OLVA: Optimal Latent V ector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation

Autor: Al Chanti, Dawood, Mateuś, Diana

Publikováno v: the 24th International Conference on Medical Image Computing and Computer Assisted Intervention
the 24th International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2021, Strasbourg (virtuel), France

International audience; This paper addresses the domain shift problem for segmentation. As a solution, we propose OLVA, a novel and lightweight unsupervised domain adaptation method based on a Variational Auto-Encoder (VAE) and optimal transport (OT)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::300738386d75f89682ae199fb80a0fef
https://hal.archives-ouvertes.fr/hal-03261428/document

Analyse Automatique des Macro et Micro Expressions Faciales : Détection et Reconnaissance par Machine Learning

Autor: Al Chanti, Dawood

Publikováno v: Signal and Image processing. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAT058⟩
Image Processing [eess.IV]. UGA (Université Grenoble Alpes), 2019. English

Facial expression analysis is an important problem in many biometric tasks, such as face recognition, face animation, affective computing and human computer interface. In this thesis, we aim at analyzing facial expressions using images and video sequ

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::6b519cd0d513b982ac2c7cc95d9926a7
https://tel.archives-ouvertes.fr/tel-02525707/document