We hope you can join us on Thursday, October 5th at 12:30pm CET for our next 1-hour webinar with Andreas Uhl on "Temporal Image Forensics: What do we actually learn in data driven approaches?"

[6:30 a.m. New-York] - [12:30 p.m. Paris] - [6:30 p.m. Beijing]

To join the webinar, please RSVP here: https://cassyni.com/events/4Y8bwmvKGH45dZ1XHUxzLd?cb=functi
*If you wish to promote a EURASIP journal special issue, conference, event, or new image/video database at an upcoming webinar, please reply to this email with additional details.

Title: Temporal Image Forensics: What do we actually learn in data driven approaches?

Abstract: The assessment of the age of a given digital image, assuming that the EXIF data is not trustworthy, has been traditionally done by analyzing sensor defects which occur and accumulate over time. In recent work, deep-learning based technology has been increasingly used for the age assessment task, which raises the question, which image features are actually used by such techniques. Moreover, (public) datasets used in corresponding experimentation might be prone to content bias, such that instead of age groups, actually content groups are created. We will report on recent results on this topic also showing the importance of XAI techniques in this field.

Bio: Andreas Uhl is a full professor at the Department of Artificial Intelligence and Human Interfaces (AIHI), University of Salzburg, where he leads the Visual Computing and Security (VISEL) Lab. His research interests are in biometrics (with emphasis on visually recorded biometric traits), media forensics and medical imaging. He has significant interest in transdisciplinary research, e.g. in aquaculture monitoring, wood industry, and digital humanities.



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