4 citations · 8 across the 8 of their papers we have counts for
10 papers
Exploiting Spatial Structure for Transductive Few-Shot Classification of Whole-Slide Images
Tiffanie Godelaine, Manon Dausort, Karim El Khoury +3
Automating the analysis of whole-slide images (WSIs), a key step in cancer diagnosis, has high clinical value, as it can reduce pathologist's workload while improving diagnosis acc…
Refining Cytology Predictions with Conditional Random Fields
Manon Dausort, Tiffanie Godelaine, Karim El Khoury +3
Vision-language models (VLMs) achieve strong zero-shot (ZS) classification on histology images but do not perform as well on cytology, whose stains and cell morphology differ marke…
Whole-Slide Image Analysis under Realistic Few-Shot Annotation Protocols
Tiffanie Godelaine, Maxime Zanella, Karim El Khoury +2
Automating the analysis of whole-slide images has high clinical value, since characterizing cancers requires examining them in detail. Such analysis increasingly relies on vision-l…
Conditional Random Fields for Interactive Refinement of Histopathological Predictions
Tiffanie Godelaine, Maxime Zanella, Karim El Khoury +3
Assisting pathologists in the analysis of histopathological images has high clinical value, as it supports cancer detection and staging. In this context, histology foundation model…
Leveraging Prediction Entropy for Automatic Prompt Weighting in Zero-Shot Audio-Language Classification
Karim El Khoury, Maxime Zanella, Tiffanie Godelaine +2
Audio-language models have recently demonstrated strong zero-shot capabilities by leveraging natural-language supervision to classify audio events without labeled training data. Ye…
Optimizing Resources for On-the-Fly Label Estimation with Multiple Unknown Medical Experts
Tim Bary, Tiffanie Godelaine, Axel Abels +1
Accurate ground truth estimation in medical screening programs often relies on coalitions of experts and peer second opinions. Algorithms that efficiently aggregate noisy annotatio…
CIA: Controllable Image Augmentation Framework Based on Stable Diffusion
Mohamed Benkedadra, Dany Rimez, Tiffanie Godelaine +6
Computer vision tasks such as object detection and segmentation rely on the availability of extensive, accurately annotated datasets. In this work, We present CIA, a modular pipeli…
Exploring Foundation Models Fine-Tuning for Cytology Classification
Manon Dausort, Tiffanie Godelaine, Maxime Zanella +3
Cytology slides are essential tools in diagnosing and staging cancer, but their analysis is time-consuming and costly. Foundation models have shown great potential to assist in the…
Enhancing Remote Sensing Vision-Language Models for Zero-Shot Scene Classification
Karim El Khoury, Maxime Zanella, Benoît Gérin +5
Vision-Language Models for remote sensing have shown promising uses thanks to their extensive pretraining. However, their conventional usage in zero-shot scene classification metho…
Streamlined Hybrid Annotation Framework using Scalable Codestream for Bandwidth-Restricted UAV Object Detection
Karim El Khoury, Tiffanie Godelaine, Simon Delvaux +2
Emergency response missions depend on the fast relay of visual information, a task to which unmanned aerial vehicles are well adapted. However, the effective use of unmanned aerial…