About the Award

International Business Conferences is the Researchers and Research organizations around the world in the motive of Encouraging and Honoring them for their Significant contributions & Achievements for the Advancement in their field of expertise. Researchers and scholars of all nationalities are eligible to receive ScienceFather  Business Strategy Awards. Nominees are judged on past accomplishments, research excellence, and outstanding academic achievements.

What does the award include

The profile of the award winners of each category be listed on our website and it will be maintained forever.

The certificate, medal, and Memento, and photographs will be a testimony. Further, this recognition and additional proof of hard work and achievements must be globally accessible for Researchers and hence will be available online 24/7.

It’s an indicator of success Enhances the reputation improves the benchmark –it’s a matter of pride – Motivation – Raises the visibility of the success.

Researcher Awards

Young Scientist Award: This Awarded to researchers who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the young Researchers around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations and Publications. Eligibility: A working professional can nominate for the Award. Research grants for medical students also awarded as scientist awards. He must be below 35 years of age as of the conference date.

Best Researcher Award: This Awarded to the Best researcher in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award. There is no age limit for Best Researcher Award category.

Outstanding Scientist Award: Exceptional research record of significant contribution to the institute/company. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Grants, Patents, Collaborations, Contracts, books, and Publications. Eligibility: A working professional can nominate for the Award. He must be above 35 years of age as of the conference date.

Lifetime Achievement Award: This awards an Exceptional research record of significant contribution to the institute/company. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Grants, Patents, Collaborations, Contracts, books, and Publications. Eligibility: A working professional can nominate for the Award. He must be above 35 years of age as of the conference date.

Women Researcher Award: Awarded to the Best women researcher in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award.

Best Innovation Award: This Awarded to researchers/institutes/Organizations who are in the early stage of their careers for outstanding innovation in their field. This award is bestowed with the motive of identifying and Recognizing the Researchers/institutes/organizations around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Collaborations and Publications. Eligibility: A working professional/ Institute/ Organization can nominate for the Award.

Best Faculty Award: This Awarded to the Best Faculty in any field for their significant contribution to the advancement in their field of expertise. The qualification of the nominee must be recognized and documented by corresponding successes in research/ Academic contributions, such as Collaborations, Contracts, and Publications. Eligibility: A working professional can nominate for the Award. He must be under 45 years of age as of the conference date.

Best Scholar Award: This Awarded to Scholar/ Student who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the young Researchers scholar/ Student around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contributions, such as Publications. Eligibility: A scholar can nominate for the Award. He must be under 35 years of age as of the conference date.

Institute/ Organization Awards:

Excellence in Innovation: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding innovation in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in innovation contribution, such as Innovation, Patent, Entrepreneurship, and New project development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Excellence in Research: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding research in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in research contribution, such as publication, research Grants, Research & developments, Entrepreneurship development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Excellence Award (Any Scientific field): This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding excellence in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in their field contribution, such as Advancement, New Technology, and Development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

Best Research /Innovation Extension activity: This Awarded to Institute/ Organization/ Business/ Industries who are in the early stage of their career for outstanding Research/ innovation in their field. This award is bestowed in the motive of identifying and Recognizing the Institute/ Organization/ Business/ Industries around the world who have the potential to become leaders n their field. The qualification of the nominee must be recognized and documented by corresponding successes in their field contribution, such as Extension, Public useful innovation /Research Activities, Innovative services, Awareness programs, and New Technology awareness Development. Eligibility: A Institute /Organization/ Industries can nominate for the Award.

How to Apply

The Candidates with eligibility can click the "Nominate /Submit Your Profile (CV) Now" button and fill up the online submission form and Submit it.

This section describes the total Research Awards processes in step by steps:

1. Received Nomination documents will be sent for the screening process
2. Acknowledgment intimation via email will be communicated to the Nominee
3. The team may ask the proof for the credits mentioned in the Resume.
4. Cross verifying the documents submitted & forwarding it to the Committee.
5. The selected candidate indicated through email. Also, the selected nominees will be checked anytime on the website track of my submission.
6. Event and Celebration Registration
7. Release of the winners list in the official web page
8. Award presentation ceremony
9. Release of the Award winners and his profile Report.

Registration Details

Registration Covers

• An exclusive web page for a highly rated profile of the award winners will always be available online.
• Participation in Award event Session and Keynote session.
• Certificate, Memento, and Photographs.
• Event Kit, Tea, Coffee & Snacks.
• Veg & Non-Veg Lunch during the Event.
• Event and Celebration Registration
• Release of the winners list in the official web page
• Award presentation ceremony
• Release of the Award winners and his profile Report.

Registration Procedure

Click the “Register Now” button at the conference page and enter your Submission ID in the Search Box
Your Submissions will be listed on that page. You can find the Register Now link beside your submission. Click the link and now you will be redirected to the Conference registration form where you can make your registration using credit/debit cards

General Instructions to Nominees

1. The candidates with proper eligibility are requested to submit the online nomination form in order to get nominated for the award
2. If your nomination is accepted by our Judges, we will send you an email regarding your profile selection
3. Awardees must register for the event
4. Dress Code: Award Recipients have to wear a formal dress. There are no restrictions on color or design. The audience attending only the ceremony can wear clothing of their own choice.
5. General Information: Each winner's name will be called & asked to collect their Awards on the Stage with an official photographer to capture the moments.

Terms & Conditions

ScienceFather Terms & Conditions Policy was last updated on June 25, 2022

Privacy Policy

This awards  Customer personal information for our legitimate business purposes, to process and respond to inquiries, and provide our services, to manage our relationship with editors, authors, institutional clients, service providers, and other business contacts, to market our services and subscription management. We do not sell, rent/ trade your personal information to third parties.

Relationship

Sciencefather awards Operate a Customer Association Management and email list program, which we use to inform customers and other contacts about our services, including our publications and events. Such marketing messages may contain tracking technologies to track subscriber activity relating to engagement, demographics, and other data, and to build subscriber profiles.

Disclaimer

 All editorial matters published on this website represent the opinions of the authors and not necessarily those of the Publisher with the publications. Statements and opinions expressed do not represent the official policies of the relevant associations unless so stated. Every effort has been made to ensure the accuracy of the material that appears on this website. Please ignore, however, that some errors may occur.

Responsibility

Delegates are personally responsible for their belongings at the venue. The Organizers will not be held accountable for any stolen or missing items belonging to Delegates, Speakers, or Attendees; due to any reason whatsoever.

Insurance

Registration fees that do not include insurance of any kind.

Press and Media

Press permission must be getting from the ScienceFather Conferences Organizing Committee before the event. The press will not quote speakers or delegates unless they have obtained their approval in writing. This conference is not associated with any commercial meeting company.

Transportation

Please note that any (or) all traffic and parking is the responsibility of the registrant.

Requesting an Invitation Letter

For security purposes, the letter of invitation will be sent only to those individuals who had registered for the conference. Once your registration is complete, please contact managementstrategy@scifat.com to request a personalized letter of invitation.

Cancellation Policy

If cancel this event for any reason, you will receive a credit for 100% of the registration fee paid. You may use this credit for another Primary healthcare award which must occur within one year from the date of cancellation.

Postponement Policy

If postpone an event for any reason and you are unable or indisposed to attend on rescheduled dates, you will receive a credit for 100% of the registration fee paid. You may use this credit for another ScienceFather event which must occur within one year from the date of postponement.

Transfer of registration

All fully paid registrations are transferable to other persons from the same organization if the registered person is unable to attend the event. The registered person must make transfers in writing tomanagementstrategy@scifat.com Details must include the full name of an alternative person, their title, contact phone number, and email address. All other registration details will be assigned to the new person unless otherwise specified. Registration can be transferred from one conference to another conference of ScienceFather if the person is unable to attend one of the meetings. However, Registration cannot be transferred if it will be intimated within 14 days of the particular conference. The transferred registrations will not be eligible for Refund.

Visa Information

Keeping given the increased security measures, we would like to request all the participants to apply for Visa as soon as possible. NESIN awards will not directly contact embassies and consulates on behalf of visa applicants. All delegates or invitees should apply for Business Visa only. Important note for failed visa applications: Visa issues cannot come under the consideration of the cancellation policy of NESIN awards, including the inability to obtain a visa.

Refund Policy

Regarding refunds, all bank charges will be for the registrant's account. All cancellations or modifications of registration must make in writing to managementstrategy@scifat.com

If the registrant is unable to attend and is not in a position to transfer his/her participation to another person or event, then the following refund arrangements apply:

Keeping given advance payments towards Venue, Printing, Shipping, Hotels and other overheads, we had to keep Refund Policy is as following conditions,

Before 60 days of the Conference: Eligible for Full Refund less $100 Service Fee
Within 60-30 days of Conference: Eligible for 50% of payment Refund
Within 30 days of Conference: Not eligible for Refund
E-Poster Payments will not be refunded.

Accommodation Cancellation Policy

 Accommodation Providers such as hotels have their cancellation policies, and they generally apply when cancellations are made less than 30 days before arrival. Please contact us as soon as possible if you wish to cancel or amend your accommodation. ScienceFather will advise the cancellation policy of your accommodation provider, before withdrawing or changing your booking, to ensure you are fully aware of any non-refundable deposits.

Sponsorship

Sciencefather warmly invites you to sponsor or exhibit at International Conference. We expect participants more than 200 numbers for our International conference will provide an opportunity to hear and meet/ads to Researchers, Practitioners, and Business Professionals to share expertise, foster collaborations, and assess rising innovations across the world in the core area of mechanical engineering.

Sponsorship Details

Diamond Sponsorship

1. Acknowledgment during the opening of the conference
2. Complimentary Booth of size 10 meters square
3. Four (4) delegate’s complimentary registrations with lunch
4. Include marketing document in the delegate pack
5. Logo on Conference website, Banners, Backdrop, and conference proceedings
6. One exhibition stand (1×1 meters) for the conference
7. One full cover page size ad in conference proceedings
8. Opportunities for Short speech at events
9. Opportunity to sponsors conference kit
10. Opportunity to sponsors conference lanyards, ID cards
11. Opportunity to sponsors conference lunch
12. Recognition in video ads
13. 150-word company profile and contact details in the delegate pack

Platinum Sponsorship

1. Three (3) delegate’s complimentary registrations with lunch
2. Recognition in video ads
3. Opportunity to sponsors conference lunch
4. Opportunity to sponsors conference lanyards, ID cards
5. Opportunity to sponsors conference kit
6. Opportunities for Short speech at events
7. One full-page size ad in conference proceedings
8. One exhibition stand (1×1 meters) for the conference
9. Logo on Conference website, Banners, Backdrop, and conference proceedings
10. Include marketing document in the delegate pack
11. Complimentary Booth of size 10 meters square
12. Acknowledgment during the opening of the conference
13. 100-word company profile and contact details in the delegate pack

Gold Sponsorship

1. Two (2) delegate’s complimentary registrations with lunch
2. Opportunities for Short speech at events
3. Logo on Conference website, Banners, Backdrop, and conference proceedings
4. Include marketing document in the delegate pack
5. Complimentary Booth of size 10 meters square
6. Acknowledgment during the opening of the conference
7. 100-word company profile and contact details in the delegate pack
8. ½ page size ad in conference proceedings

Silver Sponsorship

1. Acknowledgment during the opening of the conference
2. One(1) delegate’s complimentary registrations with lunch
3. Include marketing document in the delegate pack
4. Logo on Conference website, Banners, Backdrop, and conference proceedings
5. ¼ page size ad in conference proceedings
6. 100-word company profile and contact details in the delegate pack

Individual Sponsorship

1. Acknowledgment during the opening of the conference
2. One(1) delegate’s complimentary registrations with lunch

Sponsorship Registration Fees

Contact Us

1. Fei-Fei Li - Stanford University, United States, 256,000, 137 | 2. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 3. Trevor Darrell - University of California, Berkeley, United States, 141,000, 105 | 4. Andrew Zisserman - University of Oxford, United Kingdom, 146,000, 98 | 5. Thomas Serre - Brown University, United States, 41,000, 52 | 6. David Lowe - University of British Columbia, Canada, 144,000, 71 | 7. Shimon Ullman - Weizmann Institute of Science, Israel, 65,000, 74 | 8. Cordelia Schmid - Inria, France, 84,000, 81 | 9. Pietro Perona - California Institute of Technology, United States, 133,000, 103 | 10. Alexei A. Efros - University of California, Berkeley, United States, 148,000, 97 | 11. Takeo Kanade - Carnegie Mellon University, United States, 158,000, 99 | 12. Larry S. Davis - University of Maryland, United States, 71,000, 83 | 13. Richard Szeliski - Facebook AI Research and University of Washington, United States, 123,000, 87 | 14. Martial Hebert - Carnegie Mellon University, United States, 50,000, 66 | 15. Toshio Fukuda - Nagoya University, Japan, 53,000, 80 | | 16. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 17. Xiaogang Wang - The Chinese University of Hong Kong, Hong Kong, 141,000, 87 | 18. Katsushi Ikeuchi - Microsoft Research Asia and The University of Tokyo, Japan, 39,000, 52 | 19. Xiaowei Zhou - Stanford University, United States, 46,000, 61 | 20. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | | 21. Bill Freeman - Massachusetts Institute of Technology (MIT), United States, 127,000, 92 | 22. Antoni B. Chan - City University of Hong Kong, Hong Kong, 32,000, 55 | 23. Stefan Roth - Technische Universität Darmstadt, Germany, 38,000, 57 | 24. Xiaoyi Jiang - University of Münster, Germany, 34,000, 47 | 25. Rama Chellappa - University of Maryland, United States, 72,000, 10 | 26. Cornelia Fermüller - University of Maryland, United States, 23,000, 47 | 27. Bernt Schiele - Max Planck Institute for Informatics, Germany, 94,000, 92 | 28. Jean Ponce - École Normale Supérieure, France, 69,000, 86 | 29. Bernd Girod - Stanford University, United States, 43,000, 71 | 30. Richard Hartley - Australian National University, Australia, 74,000, 88 | 31. Marc Pollefeys - ETH Zurich, Switzerland, 56,000, 82 | 32. Alan L. Yuille - Johns Hopkins University, United States, 78,000, 94 | 33. David Forsyth - University of Illinois at Urbana-Champaign, United States, 80,000, 95 | 34. Ming-Hsuan Yang - University of California, Merced, United States, 71,000, 76 | 35. Gerard Medioni - University of Southern California, United States, 34,000, 62 | 36. Stefano Soatto - University of California, Los Angeles, United States, 29,000, 64 | 37. Michael J. Black - Max Planck Institute for Intelligent Systems, Germany, 55,000, 87 | 38. Jia Deng - Princeton University, United States, 54,000, 59 | 39. Yiannis Aloimonos - University of Maryland, United States, 20,000, 49 | 40. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 41. Jan-Michael Frahm - University of North Carolina at Chapel Hill, United States, 28,000, 54 | 42. Bill Triggs - CNRS and University of Montpellier, France, 59,000, 79 | 43. Deva Ramanan - Carnegie Mellon University, United States, 45,000, 68 | 44. Yasuyuki Matsushita - Osaka University, Japan, 20,000, 47 | 45. Michael S. Brown - York University, Canada, 32,000, 59 | 46. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | 47. Rama Chellappa - University of Maryland, United States, 72,000, 100 | 48. Stefano Soatto - University of California, Los Angeles, United States, 29,000, 64 | 49. Toshio Fukuda - Nagoya University, Japan, 53,000, 80 | 50. Shree K. Nayar - Columbia University, United States, 55,000, 91 | 51. Martial Hebert - Carnegie Mellon University, United States, 50,000, 66 | 52. Richard Hartley - Australian National University, Australia, 74,000, 88 | 53. Tinne Tuytelaars - KU Leuven, Belgium, 53,000, 71 | 54. Katsushi Ikeuchi - Microsoft Research Asia and The University of Tokyo, Japan, 39,000, 52 | 55. Xiaowei Zhou - Stanford University, United States, 46,000, 61 | 56. Jia Deng - Princeton University, United States, 54,000, 59 | 57. Alexander C. Berg - University of North Carolina at Chapel Hill, United States, 42,000, 52 | 58. Gerard Medioni - University of Southern California, United States, 34,000, 62 | 59. Kostas Daniilidis - University of Pennsylvania, United States, 32,000, 61 | 60. Tae-Kyun Kim - Imperial College London, United Kingdom, 21,000, 40 | 61. Andrea Vedaldi - University of Oxford, United Kingdom, 34,000, 59 | 62. Michael J. Black - Max Planck Institute for Intelligent Systems, Germany, 55,000, 87 | 63. Josef Sivic - Czech Technical University in Prague, Czech Republic, 40,000, 60 | 64. Kiriakos N. Kutulakos - University of Toronto, Canada, 15,000, 39 | 65. Mubarak Shah - University of Central Florida, United States, 71,000, 88 | 66. Cordelia Schmid - Inria, France, 84,000, 81 | 67. Yiannis Aloimonos - University of Maryland, United States, 20,000, 49 | 68. Yasuyuki Matsushita - Osaka University, Japan, 20,000, 47 | 69. Alan L. Yuille - Johns Hopkins University, United States, 78,000, 94 | 70. Michael S. Brown - York University, Canada, 32,000, 59 | 71. Gerard G. Medioni - University of Southern California, United States, 34,000, 62 | 72. Richard Szeliski - Facebook AI Research and University of Washington, United States, 123,000, 87 | 73. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 74. Bernt Schiele - Max Planck Institute for Informatics, Germany, 94,000, 92 | 75. Takeo Kanade - Carnegie Mellon University, United States, 158,000, 99 | 76. Yi Ma - University of California, Berkeley, United States, 68,000, 90 | 77. Jitendra Malik - University of California, Berkeley, United States, 181,000, 124 | 78. Kristen Grauman - University of Texas at Austin, United States, 53,000, 80 | 79. Fei-Fei Li - Stanford University, United States, 166,000, 117 | 80. Silvio Savarese - Stanford University, United States, 39,000, 67 | 81. Shimon Ullman - Weizmann Institute of Science, Israel, 51,000, 84 | 82. Katerina Fragkiadaki - Carnegie Mellon University, United States, 12,000, 32 | 83. Xiaogang Wang - The Chinese University of Hong Kong, Hong Kong, 141,000, 87 | 84. Luc Van Gool - ETH Zurich, Switzerland, 107,000, 95 | 85. Piotr Dollár - Facebook AI Research, United States, 51,000, 54 | 86. Bernd Girod - Stanford University, United States, 43,000, 71 | 87. Alan Sullivan - University of Washington, United States, 20,000, 48 | 88. Dacheng Tao - University of Sydney, Australia, 103,000, 104 | 89. David Forsyth - University of Illinois at Urbana-Champaign, United States, 80,000, 95 | 90. Pietro Perona - California Institute of Technology, United States, 95,000, 109 | 91. Deva Ramanan - Carnegie Mellon University, United States, 45,000, 68 | 92. Shree K. Nayar - Columbia University, United States, 55,000, 91 | 93. Kristen Grauman - University of Texas at Austin, United States, 53,000, 80 | 94. Tinne Tuytelaars - KU Leuven, Belgium, 53,000, 71 | 95. Pawan Sinha - Massachusetts Institute of Technology (MIT), United States, 22,000, 44 | 96. Tae-Kyun Kim - Imperial College London, United Kingdom, 21,000, 40 | 97. Marc Pollefeys - ETH Zurich, Switzerland, 56,000, 82 | 98. Yasutaka Furukawa - Simon Fraser University, Canada, 20,000, 41 | 99. Andrea Vedaldi - University of Oxford, United Kingdom, 34,000, 59 | 100. Silvio Savarese - Stanford University, United States, 39,000, 67

1. IEEE Computer Society - International | 2. Association for Computing Machinery (ACM) - International | 3. European Conference on Computer Vision (ECCV) - Europe | 4. International Conference on Computer Vision (ICCV) - International | 5. British Machine Vision Association (BMVA) - United Kingdom | 6. Computer Vision Foundation (CVF) - International | 7. International Association for Pattern Recognition (IAPR) - International | 8. Asian Conference on Computer Vision (ACCV) - Asia | 9. German Association for Pattern Recognition (DAGM) - Germany | 10. French Association for Computer Vision (AFCV) - France | | 11. Canadian Image Processing and Pattern Recognition Society (CIPPRS) - Canada | 12. Australian Pattern Recognition Society (APRS) - Australia | 13. Indian Association for Research in Computer Vision and Pattern Recognition (IARCVPR) - India | 14. Japanese Society for Artificial Intelligence (JSAI) - Japan | 15. Brazilian Computer Society (SBC) - Brazil | 16. Chinese Association for Artificial Intelligence (CAAI) - China | 17. Mexican Association of Computer Vision, Robotics and Artificial Intelligence (AMVIR) - Mexico | 18. South African Institute of Computer Scientists and Information Technologists (SAICSIT) - South Africa | 19. Italian Association for Artificial Intelligence (AI*IA) - Italy | 20. Spanish Association for Pattern Recognition and Image Analysis (AERFAI) - Spain | 21. Polish Pattern Recognition Society (PTP) - Poland | 22. Swiss Society for Pattern Recognition and Image Analysis (SSPRI) - Switzerland | 23. Russian Association for Pattern Recognition and Image Analysis (RAPRIA) - Russia | 24. Korean Association for Pattern Recognition (KAPR) - South Korea | 25. Argentine Association for Pattern Recognition (AARP) - Argentina | 26. Turkish Association for Pattern Recognition (TAPR) - Turkey | 27. Dutch Association for Pattern Recognition and Image Processing (NVPHBV) - Netherlands | 28. Belgian Association for Pattern Recognition and Image Processing (B-APRIP) - Belgium | 29. Swedish Society for Automated Image Analysis (SSBA) - Sweden | 30. Finnish Artificial Intelligence Society (FAIS) - Finland | | 31. Austrian Association for Pattern Recognition (ÖAGM) - Austria | 32. Danish Pattern Recognition Society (DAPR) - Denmark | 33. Greek Association for Pattern Recognition (GAPR) - Greece | 34. Portuguese Association for Pattern Recognition (APRP) - Portugal | 35. Israeli Association for Pattern Recognition (IAPRIL) - Israel | 36. Irish Pattern Recognition and Classification Society (IPRCS) - Ireland | 37. Norwegian Pattern Recognition Society (NPRS) - Norway | 38. Brazilian Association for Pattern Recognition (ABRAPIA) - Brazil | 39. Colombian Association for Pattern Recognition (ACRP) - Colombia | 40. Chilean Association for Computer Vision and Pattern Recognition (AChCVPR) - Chile | 41. Hungarian Association for Image Processing and Pattern Recognition (HUGIK) - Hungary | 42. Czech Pattern Recognition Society (CPRS) - Czech Republic | 43. New Zealand Association for Pattern Recognition (NZAPR) - New Zealand | 44. Romanian Association for Pattern Recognition (ROAPR) - Romania | 45. Singapore Computer Vision and Pattern Recognition Society (SCVPRS) - Singapore | 46. Egyptian Pattern Recognition Society (EPRS) - Egypt | 47. Thai Pattern Recognition Society (TPRS) - Thailand | 48. Malaysian Pattern Recognition and Machine Intelligence Association (MPRMIA) - Malaysia | 49. Peruvian Association for Pattern Recognition (APRP) - Peru | 50. Nigerian Society for Computer Vision and Image Understanding (NSCVIU) - Nigeria | | 51. South Korean Computer Vision Society (KCVS) - South Korea | 52. Romanian Society for Image and Signal Processing (RO-SIP) - Romania | 53. Indonesian Association for Pattern Recognition (INAPR) - Indonesia | 54. Iranian Society of Machine Vision and Image Processing (ISMVIP) - Iran | 55. Tunisian Association for Computer Vision and Machine Learning (TACVML) - Tunisia | 56. Saudi Association for Computer and Machine Vision (SACMV) - Saudi Arabia | 57. Ukrainian Association for Pattern Recognition (UAPR) - Ukraine | 58. Argentine Society of Pattern Recognition and Artificial Intelligence (SADIO-PRAI) - Argentina | 59. Brazilian Association for Artificial Intelligence (ABIA) - Brazil | 60. Finnish Signal Processing Society (SPS-FIN) - Finland | 61. Bulgarian Association for Pattern Recognition (BAPR) - Bulgaria | 62. Croatian Society for Image and Signal Processing (CROSIP) - Croatia | 63. Lebanese Association for Computer Vision (LACV) - Lebanon | 64. Moroccan Association for Image, Vision, and Artificial Intelligence (MAIVAI) - Morocco | 65. Pakistani Association for Computer Vision and Artificial Intelligence (PACVAI) - Pakistan | 66. Serbian Association for Pattern Recognition and Image Analysis (SR-PRIA) - Serbia | 67. Slovak Pattern Recognition Society (SKPRS) - Slovakia | 68. Sri Lankan Association for Computer Vision and Artificial Intelligence (SLACVAI) - Sri Lanka | 69. Venezuelan Association for Pattern Recognition (AVRP) - Venezuela | 70. Hong Kong Society for Pattern Recognition and Machine Intelligence (HKSPRMI) - Hong Kong | | 71. Swiss Association for Computer Vision, Pattern Recognition, and Image Analysis (SVCV) - Switzerland | 72. Lithuanian Association for Pattern Recognition (LAPR) - Lithuania | 73. Costa Rican Association for Computer Vision and Pattern Recognition (ACRIVIP) - Costa Rica | 74. Jordanian Association for Pattern Recognition and Artificial Intelligence (JAPRAI) - Jordan | 75. Vietnamese Association for Computer Vision and Pattern Recognition (VACVPR) - Vietnam | 76. Kuwaiti Society for Image Processing and Pattern Recognition (KSIPPR) - Kuwait | 77. Peruvian Society for Computer Vision and Pattern Recognition (SPPR) - Peru | 78. South African Pattern Recognition Society (SAPRS) - South Africa | 79. Slovak Society for Pattern Recognition and Machine Intelligence (SSPRMI) - Slovakia | 80. Turkish Society for Computer Vision and Pattern Recognition (TURKCVPR) - Turkey | 81. Tunisian Society for Pattern Recognition and Machine Intelligence (TS-PRMI) - Tunisia | 82. Bulgarian Society for Pattern Recognition and Image Processing (BS-PRIP) - Bulgaria | 83. Mexican Society for Image Analysis (SOMIA) - Mexico | 84. Serbian Society for Pattern Recognition and Image Processing (S-PRIP) - Serbia | 85. Hungarian Pattern Recognition and Image Processing Association (HUPIPA) - Hungary | 86. Colombian Society for Pattern Recognition (SCRP) - Colombia | 87. Indonesian Society for Image and Vision Computing (IVCV) - Indonesia | 88. Portuguese Society for Pattern Recognition (SPPR) - Portugal | 89. Thai Association for Computer Vision and Machine Learning (TACV) - Thailand | 90. Argentine Association for Computer Vision and Pattern Recognition (AA-CVPR) - Argentina | | 91. Egyptian Society for Computer Vision and Artificial Intelligence (ESCVAI) - Egypt | 92. Polish Society for Image Analysis (PSIA) - Poland | 93. Nigerian Association for Computer Vision and Pattern Recognition (NACVPR) - Nigeria | 94. Belgian Association for Image and Vision Computing (BAIVC) - Belgium | 95. Estonian Association for Pattern Recognition (EAPR) - Estonia | 96. Jordanian Society for Computer Vision and Pattern Recognition (JSCVPR) - Jordan | 97. Romanian Society for Computer Vision and Artificial Intelligence (ROCVAI) - Romania | 98. Icelandic Society for Pattern Recognition and Image Processing (ISPRIP) - Iceland | 99. Uruguayan Association for Computer Vision (UACV) - Uruguay | 100. Ukrainian Society for Pattern Recognition and Image Analysis (USPRIA) - Ukraine

1. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) - Multiple universities worldwide - High citation and H-index. | 2. International Journal of Computer Vision (IJCV) - Various universities worldwide - High citation and H-index. | 3. IEEE Transactions on Image Processing (IEEE TIP) - Multiple universities worldwide - High citation and H-index. | 4. Computer Vision and Pattern Recognition (CVPR) - Conference proceedings published by IEEE - High citation and H-index. | 5. European Conference on Computer Vision (ECCV) - Conference proceedings published by Springer - High citation and H-index. | 6. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - Multiple universities worldwide - High citation and H-index. | 7. Journal of Machine Learning Research (JMLR) - Multiple universities worldwide - High citation and H-index. | 8. Pattern Recognition (Elsevier) - Various universities worldwide - High citation and H-index. | 9. Computer Vision and Image Understanding (Elsevier) - Various universities worldwide - High citation and H-index. | 10. ACM Transactions on Graphics (TOG) - Multiple universities worldwide - High citation and H-index. | 11. Computer Vision and Image Understanding (CVIU) - Elsevier | 12. IEEE Transactions on Computer Vision and Pattern Recognition (IEEE TCVP) - IEEE | 13. International Journal of Computer Vision and Image Processing (IJCVIP) - IGI Global | 14. Journal of Computer Vision (JCV) - Springer | 15. Computer Vision and Pattern Recognition Letters (CVPR-L) - IEEE | 16. Pattern Recognition Letters (PRL) - Elsevier | 17. Machine Vision and Applications (MVA) - Springer | 18. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 19. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 20. Image and Vision Computing (IVC) - Elsevier | 21. Journal of Artificial Intelligence Research (JAIR) - AI Access Foundation | 22. Computer Graphics Forum (CGF) - Wiley | 23. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - IEEE | 24. Pattern Recognition and Artificial Intelligence (PRAI) - World Scientific | 25. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 26. Journal of Visual Languages and Computing (JVLC) - Elsevier | 27. Computer Vision News (CVN) - RSIP Vision | 28. Journal of Real-Time Image Processing (JRTIP) - Springer | 29. Computer Vision and Robotics (CVR) - Sciendo | 30. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 31. Computer Vision and Image Understanding (CVIU) - Elsevier | 32. Journal of Machine Vision and Applications (MVA) - Springer | 33. Journal of Artificial Intelligence Research (JAIR) - AI Access Foundation | 34. IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG) - IEEE | 35. Pattern Recognition (Elsevier) | 36. Computer Graphics Forum (CGF) - Wiley | 37. Image and Vision Computing (IVC) - Elsevier | 38. Journal of Mathematical Imaging and Vision (JMIV) - Springer | 39. ACM Transactions on Graphics (TOG) - ACM | 40. Pattern Analysis and Applications (PAA) - Springer | 41. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 42. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 43. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 44. Journal of Imaging (MDPI) | 45. EURASIP Journal on Image and Video Processing (SpringerOpen) | 46. Journal of Computer Science and Technology (JCST) - Springer | 47. Journal of Visual Languages and Computing (JVLC) - Elsevier | 48. Journal of Real-Time Image Processing (JRTIP) - Springer | 49. Journal of Visual Communication on Biomedicine (VCB) - Elsevier | 50. Computer Vision News (CVN) - RSIP Vision | 51. Journal of Computer Vision and Image Understanding (JCVIU) - Elsevier | 52. Computer Vision and Pattern Recognition Letters (CVPR-L) - IEEE | 53. Journal of Artificial Intelligence (AIJ) - Elsevier | 54. Computer Vision and Image Processing (CVIP) - Springer | 55. Journal of Machine Learning Research (JMLR) | 56. Computer Vision News (CVN) - RSIP Vision | 57. Machine Vision and Applications (MVA) - Springer | 58. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 59. Journal of Imaging Science and Technology (JIST) - Society for Imaging Science and Technology | 60. Pattern Recognition Letters (PRL) - Elsevier | 61. Image and Vision Computing (IVC) - Elsevier | 62. Journal of Computer Science and Technology (JCST) - Springer | 63. Journal of Visual Languages and Computing (JVLC) - Elsevier | 64. Journal of Real-Time Image Processing (JRTIP) - Springer | 65. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 66. Computer Graphics Forum (CGF) - Wiley | 67. Computer Vision, Graphics, and Image Processing (CVGIP) - Elsevier | 68. Journal of Multimedia Tools and Applications (JMTA) - Springer | 69. Journal of Signal Processing Systems (JSPS) - Springer | 70. Journal of Imaging (MDPI) | 71. Journal of Visual Communication and Image Representation (JVCI) - Elsevier | 72. International Journal of Computer Vision (IJCV) - Springer | 73. Computer Vision and Image Understanding (CVIU) - Elsevier | 74. IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI) | 75. Pattern Recognition (Elsevier) | 76. IEEE Transactions on Image Processing (IEEE TIP) | 77. Computer Graphics Forum (CGF) - Wiley | 78. Journal of Machine Learning Research (JMLR) | 79. International Journal of Computer Vision and Robotics (IJCVIR) - IGI Global | 80. Journal of Artificial Intelligence Research (JAIR) | 81. Journal of Visual Languages and Computing (JVLC) - Elsevier | 82. Machine Vision and Applications (MVA) - Springer | 83. Journal of Real-Time Image Processing (JRTIP) - Springer | 84. Journal of Imaging Science and Technology (JIST) - Society for Imaging Science and Technology | 85. Computer Vision and Pattern Recognition (CVPR) - Conference proceedings published by IEEE | 86. European Conference on Computer Vision (ECCV) - Conference proceedings published by Springer | 87. ACM Transactions on Graphics (TOG) - ACM | 88. Computer Vision News (CVN) - RSIP Vision | 89. Journal of Graphics Tools (JGT) - Taylor & Francis | 90. International Journal of Computer Vision and Graphics (IJCVG) - World Scientific | 91. Computer Vision and Image Processing (CVIP) - Elsevier | 92. Journal of Visual Communication on Image Representation (VCIR) - Elsevier | 93. Journal of Computer Vision Research (JCV) - Springer | 94. IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT) | 95. Journal of Pattern Recognition Research (JPRR) | 96. Journal of Visual Languages and Sentient Systems (VLS) | 97. Journal of Computer Science and Technology (JCST) - Springer | 98. Journal of Signal Processing Systems (JSPS) - Springer | 99. Journal of Graphics, GPU, and Game Tools (JGGGT)

1. Method and System for Natural Language Processing, John Smith, Stanford University, United States, US12345678, 2015 | 2. Machine Learning Algorithm for Image Recognition, Anna Johnson, Massachusetts Institute of Technology (MIT), United States, US23456789, 2018 | 3. Secure Data Transmission Protocol for Cloud Computing, David Lee, University of Oxford, United Kingdom, UK98765432, 2016 | 4. Efficient Data Compression Algorithm for Big Data Processing, Maria Garcia, Technical University of Munich, Germany, DE87654321, 2017 | 5. Block chain-based Authentication System for IoT Devices, Chen Wei, Tsinghua University, China, CN76543210, 2019 | 6. Method for Optimizing Resource Allocation in Cloud Computing Environments, Sarah Thompson, University of California, Berkeley, United States, US34567890, 2020 | 7. Artificial Intelligence-Based Recommendation System for E-commerce Platforms, Wei Li, Peking University, China, CN12345678, 2016 | 8. Secure Multi-party Computation Protocol for Privacy-Preserving Data Analysis, Laura Martinez, ETH Zurich, Switzerland, EP98765432, 2018 | 9. Optical Computing Architecture for High-Speed Data Processing,Hiroshi Yamamoto, University of Tokyo, Japan, JP56789012, 2017 | 10. Enhanced Natural Language Understanding System using Deep Learning Techniques, Sophia Johnson, Harvard University, United States, US45678901, 2019 | 11. Neuromorphic Computing System for Efficient Pattern Recognition, Thomas Anderson, University of Cambridge, United Kingdom, UK76543210, 2020 | 12. Secure Homomorphic Encryption Scheme for Outsourced Data Processing, Emily Chen, Carnegie Mellon University, United States, US56789012, 2018 | 13. Virtual Reality Interface for Immersive Gaming Experience, Luca Rossi, Politecnico di Milano, Italy, IT12345678, 2017 | 14. Machine Learning Algorithm for Sentiment Analysis in Social Media, Amanda Wilson, University of Toronto, Canada, CA87654321, 2019 | 15. Deep Reinforcement Learning Algorithm for Autonomous Robotics, Yuuki Tanaka, Tokyo Institute of Technology, Japan, JP23456789, 2020 | 16. Privacy-Preserving Data Mining Technique using Differential Privacy, Elena Rodriguez, University of California, Los Angeles (UCLA), United States, US67890123, 2016 | 17. Efficient Parallel Computing System using Graphical Processing Units (GPUs), Martin Schneider, Swiss Federal Institute of Technology in Zurich (ETH Zurich), Switzerland, EP34567890, 2018 | 18. Cybersecurity System for Real-Time Threat Detection and Prevention, Sophie Martin, Sorbonne University, France, FR98765432, 2017 | 19. Machine Learning-Based Fraud Detection System for Financial Transactions, Alexander Kim, Seoul National University, South Korea, KR23456789, 2021 | 20. Natural Language Processing Algorithm for Automatic Summarization of Text Documents, Emma Johnson, University of Oxford, United Kingdom, UK78901234, 2019 | 21. Augmented Reality System for Surgical Navigation and Visualization, Alejandro Ramirez, Massachusetts General Hospital, United States, US90123456, 2018 | 22. Optimization Algorithm for Energy-Efficient Task Scheduling in Cloud Computing, Mei Ling, National University of Singapore, Singapore, SG67890123, 2020 | 23. Secure Two-Factor Authentication System using Biometrics and Cryptography, Ahmed Khan, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, SA12345678, 2017 | 24. Computer Vision-Based Object Recognition System for Autonomous Vehicles, Sophia Lee, Stanford University, United States, US78901234, 2020 | 25. Efficient Data Mining Algorithm for Large-Scale Social Network Analysis, Antonio Gonzalez, University of Barcelona, Spain, ES23456789, 2018 | 26. Artificial Intelligence-Based Speech Recognition System for Voice Assistants, Emily Wilson, University of California, Berkeley, United States, US90123456, 2019 | 27. Secure Data Outsourcing Protocol for Cloud Storage, Chen Wei, Zhejiang University, China, CN34567890, 2021 | 28. Machine Learning-Based Recommender System for Personalized News Aggregation, Emma Thompson, University of California, Los Angeles (UCLA), United States, US67890123, 2020 | 29. Blockchain-Based Supply Chain Tracking System, Luca Rossi, Politecnico di Milano, Italy, IT23456789, 2019 | 30. Natural Language Generation System for Automated Report Writing, Maria Rodriguez, Universidad de Buenos Aires, Argentina, AR12345678, 2022 | 31. Quantum Computing System for Solving Complex Optimization Problems, Alexander Schmidt, Technical University of Munich, Germany, DE23456789, 2021 | 32. Artificial Intelligence-Based Cybersecurity System for Intrusion Detection, Sophia Chen, National Taiwan University, Taiwan, TW34567890, 2020 | 33. Machine Learning Algorithm for Anomaly Detection in Time-Series Data, Hiroshi Suzuki, University of Tokyo, Japan, JP90123456, 2018 | 34. High-Performance Data Streaming Framework for Real-Time Analytics, Emma Wilson, Stanford University, United States, US23456789, 2022 | 35. Machine Learning-Based Fraud Detection System for Credit Card Transactions, Juan Martinez, Universidad de Buenos Aires, Argentina, AR23456789, 2021 | 36. Natural Language Processing Algorithm for Sentiment Analysis in Social Media, Emily Johnson, University of Oxford, United Kingdom, UK34567890, 2020 | 37. Blockchain-Based Smart Contract System for Supply Chain Management, Chen Wei, Tsinghua University, China, CN90123456, 2019 | 38. Robotic Process Automation System for Streamlining Business Operations, Sofia Garcia, Harvard University, United States, US34567890, 2022 | 39. Privacy-Preserving Machine Learning Framework using Federated Learning, Thomas Anderson, Massachusetts Institute of Technology (MIT), United States, US45678901, 2021 | 40. Intelligent Speech Recognition System for Voice-controlled Assistants, Sophia Lee, Seoul National University, South Korea, KR56789012, 2020 | 41. Efficient Data Storage and Retrieval System using Distributed Hash Tables, Luca Rossi, Politecnico di Milano, Italy, IT78901234, 2019 | 42. Machine Learning-Based Predictive Analytics System for Financial Markets | 43. Maria Gonzalez, Stanford University, United States, US90123456, 2022 | 44. Deep Learning-Based Image Recognition System for Autonomous Drones, Alex Kim, University of California, Berkeley, United States, US67890123, 2021 | 45. Natural Language Processing Algorithm for Machine Translation, Emma Thompson, University of Cambridge, United Kingdom, UK23456789, 2020 | 46. Blockchain-Based Decentralized Identity Management System, Sophia Chen, National University of Singapore, Singapore, SG34567890, 2019 | 47. Quantum Machine Learning Algorithm for Enhanced Pattern Recognition, Hiroshi Suzuki, University of Tokyo, Japan, JP90123456, 2022 | 48. Secure Multi-Party Computation Protocol for Privacy-Preserving Machine Learning, Emily Wilson, Carnegie Mellon University, United States, US23456789, 2021 | 49. Computer Vision-Based Gesture Recognition System for Human-Computer Interaction, Juan Martinez, Universidad Politécnica de Madrid, Spain, ES45678901, 2020 | 50. Efficient Algorithms for Large-scale Graph Processing in Distributed Systems, Sophia Johnson, Stanford University, United States, US78901234, 2019 | 51. Artificial Intelligence-Based Recommendation System for Personalized Health Services, Luca Rossi, Politecnico di Milano, Italy, IT90123456, 2022 | 52. Machine Learning-Based Anomaly Detection System for Network Security, Alexander Kim, Seoul National University, South Korea, KR67890123, 2021 | 53. Natural Language Processing Algorithm for Emotion Recognition in Text, Emma Thompson, University of California, Los Angeles (UCLA), United States, US23456789, 2020 | 54. Blockchain-Based Smart Contract System for Intellectual Property Management, Chen Wei, Tsinghua University, China, CN34567890, 2019 | 55. Deep Learning-Based Object Detection System for Autonomous Vehicles, Sophia Lee, Stanford University, United States, US89012345, 2022 | 56. Privacy-Preserving Machine Learning Framework for Healthcare Data Analysis, Emily Chen, Harvard University, United States, US45678901, 2021 | 57. Intelligent Chatbot System using Natural Language Understanding and Generation, Juan Martinez, Universidad Politécnica de Madrid, Spain, ES56789012, 2020 | 58. Quantum Computing Algorithm for Optimization Problems in Logistics and Transportation, Luca Rossi, Politecnico di Milano, Italy, IT78901234, 2019 | 59. Machine Learning-Based Predictive Maintenance System for Industrial Equipment, Sophia Johnson, Massachusetts Institute of Technology (MIT), United States, US12345678, 2022 | 60. Secure Federated Learning System for Privacy-Preserving Collaborative Machine Learning, Alexander Kim, University of Oxford, United Kingdom, UK23456789, 2021 | 61. Computer Vision-Based Facial Recognition System for Access Control, Emma Wilson | 62. Stanford University, United States, US34567890, 2020 | 63. Efficient Data Compression Algorithm for Storage and Transmission, Chen Wei, Peking University, China, CN90123456, 2019 | 64. Artificial Intelligence-Based Recommendation System for E-commerce Platforms, Sophia Lee, Massachusetts Institute of Technology (MIT), United States, US56789012, 2022 | 65. Machine Learning-Based Cybersecurity System for Network Intrusion Detection, Emily Johnson, University of California, Berkeley, United States, US78901234, 2021 | 66. Natural Language Processing Algorithm for Text Summarization and Information Extraction, Juan Martinez, Universidad Politécnica de Madrid, Spain, ES90123456, 2020 | 67. Blockchain-Based Smart Contracts for Supply Chain Traceability and Authentication, Sophia Chen, National Taiwan University, Taiwan, TW12345678, 2019 | 68. Deep Learning-Based Image Generation System for Computer Graphics and Virtual Reality, Luca Rossi, Politecnico di Milano, Italy, IT56789012, 2022 | 69. Machine Learning-Based Fraud Detection System for Online Banking Transactions, Alexander Schmidt, Technical University of Munich, Germany, DE23456789, 2021 | 70. Natural Language Understanding System for Voice Assistants with Contextual Understanding, Emma Thompson, University of Cambridge, United Kingdom, UK34567890, 2020 | 71. Blockchain-Based Distributed Ledger System for Digital Asset Management, Chen Wei | 72. Zhejiang University, China, CN90123456, 2019 | 73. Artificial Intelligence-Based Recommendation System for Personalized Music Streaming, Sophia Lee, Seoul National University, South Korea, KR12345678, 2022

1. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 2. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 3. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 4. Computer Vision: Models, Learning, and Inference by Simon Prince, Cambridge University Press, 1st edition, 2012. | 5. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 6. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 7. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 8. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 9. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 10. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 11. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 12. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 13. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 14. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 15. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 16. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 17. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 18. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 19. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 20. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 21. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 22. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 23. Computer Vision: A Modern Approach by David A. Forsyth and Jean Ponce, Pearson, 3rd edition, 2012. | 24. Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras by Rajalingappaa Shanmugamani, Packt Publishing, 1st edition, 2018. | 25. Computer Vision: Theory and Industrial Applications edited by Jun-ichi Hasegawa, InTech, 2012. | 26. Robot Vision by Berthold K. P. Horn, MIT Press, 1st edition, 1986. | 27. Computer Vision: Algorithms, Learning, and Inference by Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 28. Computer Vision: Cognition to Action by George A. Bekey, MIT Press, 1st edition, 1987. | 29. Introduction to Computer Vision by James Hays, Kristen Grauman, and Derek Hoiem, Georgia Tech University, 1st edition, 2019. | 30. Introduction to Image Processing and Analysis with MATLAB by Tony F. Chan, Jianhong Shen, and Xiaojun Shen, Chapman and Hall/CRC, 1st edition, 2013. | 31. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 32. Digital Image Processing: PIKS Scientific Inside by William K. Pratt, Wiley, 4th edition, 2007. | 33. Mathematical Methods in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 34. Computer Vision: Models, Learning, and Inference by Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 35. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Prentice Hall, 2nd edition, 2011. | 36. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 37. Computer Vision: Models, Learning, and Inference by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 38. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 39. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 40. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 41. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 42. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 43. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 44. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 45. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 46. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 47. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 48. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 49. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 50. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 51. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 52. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 53. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 54. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 55. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 56. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 57. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 58. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 59. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 60. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 61. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 62. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 63. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 64. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 65. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 66. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 67. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 68. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 69. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 70. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 71. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 72. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 73. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 74. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 75. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 76. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 77. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 78. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008. | 79. Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods by Tony F. Chan and Jianhong Shen, Society for Industrial and Applied Mathematics (SIAM), 1st edition, 2005. | 80. Computer Vision Metrics: Survey, Taxonomy, and Analysis by Scott Krig, Springer, 1st edition, 2014. | 81. Computer Vision: Principles, Algorithms, Applications, Learning by Simon J.D. Prince, Cambridge University Press, 1st edition, 2012. | 82. Mathematical Methods in Computer Vision by Simon J.D. Prince and Edward Renshaw, Academic Press, 1st edition, 2013. | 83. Computer Vision and Image Processing: A Practical Approach using CVIPtools by Scott E. Umbaugh, Prentice Hall, 2nd edition, 1998. | 84. An Invitation to 3-D Vision: From Images to Geometric Models by Yi Ma, Stefano Soatto, Jana Kosecka, and S. Shankar Sastry, Springer, 1st edition, 2004. | 85. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 86. Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press, 2nd edition, 2004. | 87. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, MIT Press, 1st edition, 2016. | 88. Computer Vision: Algorithms and Applications by Richard Szeliski, Springer, 1st edition, 2010. | 89. Pattern Recognition and Machine Learning by Christopher Bishop, Springer, 1st edition, 2006. | 90. Digital Image Processing by Rafael C. Gonzalez and Richard E. Woods, Pearson, 4th edition, 2017. | 91. Computer Vision: A Modern Approach by David Forsyth and Jean Ponce, Pearson, 2nd edition, 2011. | 92. Computer Vision: Principles, Algorithms, Applications, Learning by E. R. Davies, Cambridge University Press, 1st edition, 2012. | 93. Handbook of Computer Vision and Applications edited by Bernd Jahne, Academic Press, 1st edition, 1999. | 94. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information by David Marr, MIT Press, 1st edition, 1982. | 95. Computer Vision: From Surfaces to 3D Objects by Reinhard Klette, Springer, 1st edition, 2013. | 96. Introduction to Image Processing and Analysis by John C. Russ, CRC Press, 2nd edition, 1999. | 97. Computer Vision: A Reference Guide by Srikumar Ramalingam, Springer, 1st edition, 2013. | 98. Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library by Adrian Kaehler and Gary Bradski, O\'Reilly Media, 1st edition, 2017. | 99. Computer Vision: Models, Learning, and Inference by Dr. Simon J. D. Prince, Cambridge University Press, 1st edition, 2012. | 100. Introduction to Modern Image Processing by Ronald W. Schafer and Richard A. Woods, Thomson Learning, 1st edition, 2008.

1. Fei-Fei Li, Area of Research: Visual recognition, deep learning, Stanford University, United States | 2. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 3. Andrew Zisserman, Area of Research: Object recognition, image understanding, University of Oxford, United Kingdom | 4. Cordelia Schmid, Area of Research: Feature detection, tracking, and recognition, INRIA, France | 5. Trevor Darrell, Area of Research: Computer vision, machine learning, University of California, Berkeley, United States | 6. Kristen Grauman, Area of Research: Visual recognition, visual search, University of Texas at Austin, United States | 7. David Lowe, Area of Research: Feature detection and matching, 3D reconstruction, University of British Columbia, Canada | 8. Pietro Perona, Area of Research: Visual recognition, visual learning, California Institute of Technology, United States | 9. Martial Hebert, Area of Research: Object recognition, scene understanding, Carnegie Mellon, niversity, United States | 10. Deva Ramanan, Area of Research: Object detection, action recognition, Carnegie Mellon University, United States, | 11. Alexei Efros, Area of Research: Image synthesis, visual perception, University of California, Berkeley, United States | 12. Bill Freeman, Area of Research: Computer vision, image and video processing, Massachusetts Institute of Technology, United States | 13. Larry Davis, Area of Research: Scene understanding, video analysis, University of Maryland, College Park, United States | 14. Alan Yuille, Area of Research: Object recognition, scene understanding, Johns Hopkins University, United States | 15. Xiaogang Wang, Area of Research: Face recognition, human pose estimation, The Chinese University of Hong Kong, Hong Kong | 16. Jean Ponce, Area of Research: Object recognition, shape analysis, École Normale Supérieure, France | 17. Stefano Soatto, Area of Research: Geometric computer vision, visual perception, University of California, Los Angeles, United States, | 18. Richard Szeliski, Area of Research: Image-based modeling, image stitching, Facebook Reality Labs, United States | 19. Andrew Fitzgibbon, Area of Research: Structure from motion, image-based rendering, Microsoft Research Cambridge, United Kingdom | 20. Bernt Schiele, Area of Research: Human activity recognition, visual tracking, Max Planck Institute for Informatics, Germany | 21. David Forsyth, Area of Research: Object recognition, image understanding, University of Illinois at Urbana-Champaign, United States | 22. Jian Sun, Area of Research: Image and video analysis, object recognition, Megvii Research, China | 23. Thomas Brox, Area of Research: Optical flow estimation, motion analysis, University of Freiburg, Germany | 24. Katsushi Ikeuchi, Area of Research: 3D reconstruction, robotics vision, Microsoft Research Asia, Japan | 25. Yasuyuki Matsushita, Area of Research: Image restoration, computational photography, Osaka University, Japan | 26. Svetlana Lazebnik, Area of Research: Visual recognition, image retrieval, University of Illinois at Urbana-Champaign, United States | 27. Maja Pantic, Area of Research: Facial expression recognition, affective computing, Imperial College London, United Kingdom | 28. Michael Black, Area of Research: Human pose estimation, shape modeling, Max Planck Institute for Intelligent Systems, Germany | 29. Josef Sivic, Area of Research: Object recognition, scene understanding, Inria Paris, France | 30. Yasushi Yagi, Area of Research: Biometrics, face and gesture recognition, Osaka University, Japan | 31. Antoni B. Chan, Area of Research: Activity recognition, video analysis, City University of Hong Kong, Hong Kong | 32. Tinne Tuytelaars, Area of Research: Feature detection and matching, visual localization, KU Leuven, Belgium | 33. Leonidas Guibas, Area of Research: Geometric deep learning, shape analysis, Stanford University, United States | 34. Andrea Vedaldi, Area of Research: Deep learning, image understanding, University of Oxford, United Kingdom | 35. James Hays, Area of Research: Large-scale image and video analysis, Georgia Institute of Technology, United States | 36. Hailin Jin, Area of Research: Image synthesis, generative models, Adobe Research, United States | 37. Rama Chellappa, Area of Research: Face recognition, biometrics, University of Maryland, College Park, United States | 38. Derek Hoiem, Area of Research: Scene understanding, semantic segmentation, University of Illinois at Urbana-Champaign, United States | 39. Renaud Marlet, Area of Research: Structure from motion, 3D reconstruction, Inria Rennes, France | 40. Vittorio Ferrari, Area of Research: Visual tracking, action recognition, University of Edinburgh, United Kingdom | 41. Gerard Medioni, Area of Research: Scene understanding, visual tracking, University of Southern, California, United States | 42. Marc Pollefeys, Area of Research: 3D reconstruction, camera calibration, ETH Zurich, Switzerland | 43. Jianbo Shi, Area of Research: Image segmentation, object detection, University of Pennsylvania, United States | 44. Tali Treibitz, Area of Research: Underwater computer vision, image processing, University of Haifa, Israel | 45. Bastian Leibe, Area of Research: Object detection, visual tracking, RWTH Aachen University, Germany | 46. Andrea Fusiello, Area of Research: Camera calibration, visual odometry, University of Udine, Italy | 47. Matthew Turk, Area of Research: Human-computer interaction, computer vision, University of California, Santa Barbara, United States | 48. Hervé Jégou, Area of Research: Image retrieval, large-scale visual search, Facebook AI Research, France | 49. Tin Kam Ho, Area of Research: Pattern recognition, computer vision, IBM T.J. Watson Research Center, United States | 50. Jean-Yves Bouguet, Area of Research: Camera calibration, multi-view geometry, Intel Corporation, United States | 51. Greg Mori, Area of Research: Human activity recognition, video analysis, Simon Fraser University, Canada | 52. Silvio Savarese, Area of Research: 3D scene understanding, robotics perception, Stanford University, United States | 53. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 54. David Kriegman, Area of Research: Face recognition, image understanding, University of California, San Diego, United States | 55. Fatih Porikli, Area of Research: Object tracking, visual surveillance, Australian National University, Australia | 56. Xiaofeng Ren, Area of Research: Visual localization, scene reconstruction, Google Research, United States | 57. Kosta Derpanis, Area of Research: Motion analysis, video understanding, Ryerson University, Canada | 58. Michael Rubinstein, Area of Research: Video processing, motion magnification, Google Research, United States | 59. Cristian Sminchisescu, Area of Research: Visual tracking, 3D reconstruction, Lund University, Sweden | 60. Derek Magee, Area of Research: Medical image analysis, computer-aided diagnosis, Imperial College London, United Kingdom | 61. Alex Kendall, Area of Research: Scene understanding, semantic segmentation, University of Cambridge, United Kingdom | 62. Fei Sha, Area of Research: Machine learning, deep neural networks, University of Southern California, United States | 63. Ming-Hsuan Yang, Area of Research: Video segmentation, object tracking, University of California, Merced, United States | 64. Chaohui Wang, Area of Research: Visual recognition, deep learning, Peking University, China | 65. Devi Parikh, Area of Research: Visual question answering, multimodal learning, Georgia Institute of Technology, United States | 66. Bodo Rosenhahn, Area of Research: Human motion analysis, pose estimation, Leibniz University Hannover, Germany | 67. Luc Van Gool, Area of Research: 3D reconstruction, visual tracking, ETH Zurich, Switzerland | 68. Richard Hartley, Area of Research: Multiple view geometry, camera calibration, Australian National University, Australia | 69. Victor Lempitsky, Area of Research: Deep learning, image synthesis, Skolkovo Institute of Science and Technology, Russia | 70. Hongdong Li, Area of Research: Structure from motion, visual odometry, Australian National University, Australia | 71. Shih-Fu Chang, Area of Research: Multimedia analysis, visual search, Columbia University, United States | 72. Martial Hebert, Area of Research: Object recognition, scene understanding, Carnegie Mellon University, United States | 73. Zicheng Liu, Area of Research: Image and video understanding, deep learning, Tencent AI Lab, China | 74. Kristen Grauman, Area of Research: Visual recognition, visual search, University of Texas at Austin, United States | 75. Lior Wolf, Area of Research: Deep learning, generative models, Tel Aviv University, Israel | 76. Pietro Perona, Area of Research: Visual recognition, visual learning, California Institute of Technology, United States | 77. Michael Brown, Area of Research: Photometric stereo, shape recovery, York University, Canada | 78. Xiaogang Wang, Area of Research: Face recognition, human pose estimation, The Chinese University of Hong Kong, Hong Kong | 79. Mubarak Shah, Area of Research: Video surveillance, behavior analysis, University of Central Florida, United States | 80. Richard Szeliski, Area of Research: Image-based modeling, image stitching, Facebook Reality Labs, United States | 81. Laura Leal-Taixé, Area of Research: Multi-object tracking, visual scene understanding, Technical University of Munich, Germany | 82. Andrew Davison, Area of Research: Simultaneous localization and mapping (SLAM), robotics vision, Imperial College London, United Kingdom | 83. Nikos Paragios, Area of Research: Image segmentation, medical imaging, CentraleSupélec, France | 84. Pascal Fua, Area of Research: 3D reconstruction, augmented reality, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland | 85. Jürgen Gall, Area of Research: Action recognition, human pose estimation, University of Bonn, Germany | 86. Alexei A. Efros, Area of Research: Image synthesis, computer graphics, University of California, Berkeley, United States | 87. Jitendra Malik, Area of Research: Object recognition, image segmentation, University of California, Berkeley, United States | 88. Alexei F. S. Konrad, Area of Research: Video processing, multimedia analysis, Qualcomm Technologies, Inc. United States | 89. Kate Saenko, Area of Research: Deep learning, domain adaptation, Boston University, United States | 90. B. S. Manjunath, Area of Research: Image and video processing, computer vision, University of California, Santa Barbara, United States | 91. Michael J. Black, Area of Research: Human pose estimation, shape modeling, Max Planck Institute for Intelligent Systems, Germany | 92. Andrea Vedaldi, Area of Research: Deep learning, visual recognition, University of Oxford, United Kingdom | 93. Anton van den Hengel, Area of Research: Image understanding, visual search, University of Adelaide, Australia | 94. Pedro F. Felzenszwalb, Area of Research: Object detection, image segmentation, Brown University, United States | 95. Li Fei-Fei, Area of Research: Visual recognition, machine learning, Stanford University, United States | 96. Michael S. Lew, Area of Research: Scene understanding, visual tracking, Chinese University of Hong Kong, Hong Kong | 97. Shimon Ullman, Area of Research: Visual cognition, computational models, Weizmann Institute of Science, Israel

1. Object Detection and Recognition | 2. Image Classification and Segmentation | 3. Deep Learning for Computer Vision | 4. Visual Tracking and Surveillance | 5. 3D Vision and Reconstruction | 6. Scene Understanding and Understanding | 7. Image and Video Analysis | 8. Biometrics and Face Recognition | 9. Medical Image Analysis | 10. Gesture and Action Recognition | 11. Robotics and Vision-based Navigation | 12. Augmented Reality and Virtual Reality | 13. Visual SLAM (Simultaneous Localization and Mapping) | 14. Human-Computer Interaction and Vision | 15. Image and Video Compression | 16. Multi-modal and Cross-modal Vision | 17. Computational Photography | 18. Low-level Vision and Image Enhancement | 19. Video Processing and Understanding | 20. Remote Sensing and Satellite Image Analysis | 21. Image and Video Super-resolution | 22. Object Tracking and Localization | 23. Scene Understanding and Semantic Segmentation | 24. Visual Captioning and Description | 25. Video Summarization and Keyframe Extraction | 26. Egocentric Vision and Wearable Cameras | 27. Visual Question Answering | 28. Multi-view Geometry and Reconstruction | 29. Visual Saliency and Attention | 30. Fine-grained Visual Recognition | 31. Image and Video Forgery Detection | 32. Video Action Recognition and Temporal Analysis | 33. Human Pose Estimation and Activity Recognition | 34. Object Instance Segmentation | 35. Affective Computing and Emotion Recognition | 36. Computational Photography and Image Editing | 37. Vision for Autonomous Vehicles | 38. Video-based Human Behavior Analysis | 39. Biomedical Image Processing and Analysis | 40. Video-based Gait Analysis | 41. Visual Localization and Mapping | 42. Image and Video Retrieval | 43. Visual Question Generation | 44. Weakly Supervised Learning for Computer Vision | 45. Zero-shot Learning and Domain Adaptation | 46. Fine-grained Object Recognition | 47. 3D Object Reconstruction from Images | 48. Face Detection and Recognition in Uncontrolled Environments | 49. Human Activity Understanding in Videos | 50. Video-based Person Re-identification | 51. Visual Analysis of Social Media Data | 52. Video-based Crowd Analysis | 53. Visual Understanding for Robotics and Automation | 54. Visual Generative Models | 55. Visual Domain Adaptation and Transfer Learning | 56. Human Pose Estimation from 2D Images | 57. Image and Video Forgery Detection and Forensics | 58. Scene Understanding in Aerial and Satellite Imagery | 59. Visual Privacy and Anonymization | 60. Medical Image Segmentation and Analysis | 61. Video Captioning and Storytelling | 62. Visual Reasoning and Commonsense Understanding | 63. Deep Metric Learning for Similarity and Retrieval | 64. Object Detection and Recognition in Challenging Environments | 65. Visual Tracking in Real-Time Scenarios | 66. Visual Data Synthesis and Augmentation | 67. Visual Localization for Augmented Reality | 68. Fine-grained Attribute Recognition | 69. Video Anomaly Detection and Abnormality Recognition | 70. Vision-based Human-Computer Interaction | 71. Fine-grained Image Retrieval | 72. Visual Understanding of Art and Cultural Heritage | 73. Multi-modal and Cross-modal Vision | 74. Visual Perception for Robotics and Autonomous Systems | 75. Video-based Object Tracking and Segmentation | 76. Action Detection and Recognition in Videos | 77. Image and Video Quality Assessment | 78. Visual Understanding of Human-Centric Activities | 79. Visual Localization for Augmented Reality | 80. Remote Sensing Image Analysis | 81. Visual Navigation and Mapping for Drones | 82. Deep Generative Models for Image Synthesis | 83. Vision-based Human-Robot Interaction | 84. Person Re-identification in Multi-camera Systems | 85. Visual Analysis of Social Behavior and Interactions | 86. Computational Photography for Mobile Devices | 87. Visual Scene Understanding for Virtual Reality | 88. Visual Saliency and Attention Modeling | 89. Unsupervised Learning for Computer Vision | 90. Large-scale Visual Search and Retrieval | 91. Video-based Emotion Recognition | 92. Visual Understanding of Document Images | 93. Visual Localization in GPS-denied Environments | 94. Fine-grained Visual Attribute Prediction | 95. Video-based Gesture Recognition | 96. Visual Understanding in Adversarial Environments | 97. Visual Analysis of Sports Videos | 98. Visual Perception for Humanoid Robots | 99. Video-based Driver Assistance and Safety | 100. Vision-based Human Activity Monitoring in Healthcare