SHyNE (ESR 2022):
Interdisciplinary applications of deep learning and material science to develop new material being more resistant to corrosion of Hydrogen.
Interdisciplinary applications of deep learning and material science to develop new material being more resistant to corrosion of Hydrogen.
The IDECYS+ project aims to develop a new flexible and secure digital solution integrating into the facial identification system for detecting facial attacks presented by printed photo, video or 3D masks.
Analysis of document images based on superivsed/self-supervised, multimodal learning and multitask learning for document images classification and document attributes classification.
Realization of an electronic signature platform with mobile telephone based on face recognition using deep learning at a high level of validity.
Social affects discrimination using combined acoustic and visual information in the multicultural environment (Japanese/French).
Application Demos for face recognition, facial expression recognition, Hand/Head/Cap/Road defect Detections.