Biometrics has become a burgeoning research area due to the industrial and government needs for authentication, identification, security, and privacy concerns. Biometric technology has become useful solution for various applications including access control, surveillance and privacy, hardware security and forensics. During last decade, Deep Learning (DL) has received a great attention to solve difficult and complex problems in various domains. Its ability to automatically learn features from big data has made it a major asset.This workshop aims to present and discuss the recent advances on deep learning applied to biometrics providing innovative solutions to challenging problems in biometrics. It is an opportunity to bring researchers and experts together to discuss the current and future state of biometrics.
Topics of interest include, but are not limited to, the following:
- DL for biometrics-based authentication and identification
- Deep biometric feature extraction
- Deep biometric feature fusion
- DL for biometric data analytics (signal, image, video, ...)
- DL for biometric spoofing and deepfake detection
- DL for big data challenges in biometrics
- DL for multimodal biometrics
- DL for soft biometrics
- DL for forensic biometrics
- DL for biometric security and privacy
- Leveraging DL techniques for biometrics
- Generative AI in biometrics
- Federated learning in biometrics
- Related applications Discipline scientifique :
Informatique - Intelligence artificielle - Vision par ordinateur et reconnaissance de formes - Traitement du signal et de l'image