In 2021 the FBTI (Fachbereichstag Informatik) Award is granted to a researcher, who expressed through his work a wider perspective
EAB Virtual Events Series – Demographic Fairness in Biometric Systems
EAB Virtual Events Series – Demographic Fairness in Biometric Systems Algorithmic decision systems have frequently been labelled as “biased”, “racist”,
Karina Knudsen defended her Master Thesis on Improving Fingerprint Presentation Attack Detection using Deep Learning and Computer Vision
Karina Knudsen defended her Master Thesis on Improving Fingerprint Presentation Attack Detection using Deep Learning and Computer Vision The purpose
Ulrich Scherhag defended his PhD thesis ‚Face Morphing and Morphing Attack Detection‘
Ulrich Scherhag successfully defended his Ph.D. thesis with the title „Face Morphing and Morphing Attack Detection“ on November 16th 2020.
Call for Chapters – Handbook of Digital Face Manipulation and Detection – From DeepFakes to Morphing Attacks
We are pleased to invite you to contribute a chapter to the first Edition of the book “Handbook of Digital
Fabian Stockhardt defended his Bachelor Thesis on Accelerating Facial Identification with Morphing
Despite steadily increasing computational power, increasing numbers of subjects in data sets can cause identification systems such as face recognition
Juan Tapia and Sebastian Gonzales are Livedet 2020 winner
The team formed by Juan Tapia and Sebastian Gonzales from Chile are the Livedet 2020 winner (http://www.iris2020.livdet.org/). Livedet 2020 competition
Andreas Nautsch wins the European Biometrics Awards 2020
In 2020 for the second time the EAB Max Snijder Award is granted to a researcher, who expressed through his
Felix Ohms defended his Bachelor Thesis on Integrated Quality Assessment of mobile touchless Fingerprint capturing using Android Smartphones
Felix Ohms defended his Bachelor Thesis on Integrated Quality Assessment of mobile touchless Fingerprint Capturing using Android Smartphones In
Dominik Böttinger defended his Bachelor Thesis on the Influence of the color channels on the detection from Adversarial Samples
Durch die steigende Verwendung autonomer Systeme zur Authentifizierung von Bildern z.B. in den Bereichen der Gesichtserkennung oder dem autonomen Fahren