9 papers · 1 filter
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…
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…
Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for Histology
Alexis Guichemerre, Soufiane Belharbi, Tsiry Mayet +4
Given the emergence of deep learning, digital pathology has gained popularity for cancer diagnosis based on histology images. Deep weakly supervised object localization (WSOL) mode…
CoLo-CAM: Class Activation Mapping for Object Co-Localization in Weakly-Labeled Unconstrained Videos
Soufiane Belharbi, Shakeeb Murtaza, Marco Pedersoli +3
Leveraging spatiotemporal information in videos is critical for weakly supervised video object localization (WSVOL) tasks. However, state-of-the-art methods only rely on visual and…
F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling
Soufiane Belharbi, Aydin Sarraf, Marco Pedersoli +3
Class Activation Mapping (CAM) methods have recently gained much attention for weakly-supervised object localization (WSOL) tasks. They allow for CNN visualization and interpretati…