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Adaptation of Weakly Supervised Localization in Histopathology by Debiasing Predictions
Alexis Guichemerre, Banafsheh Karimian, Soufiane Belharbi +6
Weakly Supervised Object Localization (WSOL) models enable joint classification and region-of-interest localization in histology images using only image-class supervision. When dep…
Uni-DAD: Unified Distillation and Adaptation of Diffusion Models for Few-step Few-shot Image Generation
Yara Bahram, Mélodie Desbos, Mohammadhadi Shateri +1
Diffusion models (DMs) produce high-quality images, yet their sampling remains costly when adapted to new domains. Distilled DMs are faster but typically remain confined within the…
CLIP-IT: CLIP-based Pairing for Histology Images Classification
Banafsheh Karimian, Giulia Avanzato, Soufian Belharbi +4
Multimodal learning has shown promise in medical imaging, combining complementary modalities like images and text. Vision-language models (VLMs) capture rich diagnostic cues but of…
PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI Localization
Alexis Guichemerre, Soufiane Belharbi, Mohammadhadi Shateri +2
Weakly supervised object localization (WSOL) methods allow training models to classify images and localize ROIs. WSOL only requires low-cost image-class annotations yet provides a…