4 papers
Federated Vision Transformer with Adaptive Focal Loss for Medical Image Classification
Xinyuan Zhao, Yihang Wu, Ahmad Chaddad +2
While deep learning models like Vision Transformer (ViT) have achieved significant advances, they typically require large datasets. With data privacy regulations, access to many or…
Towards a Transparent and Interpretable AI Model for Medical Image Classifications
Binbin Wen, Yihang Wu, Tareef Daqqaq +1
The integration of artificial intelligence (AI) into medicine is remarkable, offering advanced diagnostic and therapeutic possibilities. However, the inherent opacity of complex AI…
Enhancing Dual Network Based Semi-Supervised Medical Image Segmentation with Uncertainty-Guided Pseudo-Labeling
Yunyao Lu, Yihang Wu, Ahmad Chaddad +2
Despite the remarkable performance of supervised medical image segmentation models, relying on a large amount of labeled data is impractical in real-world situations. Semi-supervis…
FAA-CLIP: Federated Adversarial Adaptation of CLIP
Yihang Wu, Ahmad Chaddad, Christian Desrosiers +2
Despite the remarkable performance of vision language models (VLMs) such as Contrastive Language Image Pre-training (CLIP), the large size of these models is a considerable obstacl…