4 citations · 4 across the 4 of their papers we have counts for
6 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…
Locally Consistent Transductive Information Maximization for Few-Shot Remote Sensing Scene Classification
Karim El Khoury, Benoît Gérin, Benoît Macq +1
Remote sensing scene classification is increasingly relying on foundation models pre-trained on large-scale Earth-observation data. Moreover, transductive inference, which exploits…
Few-Shot Adaptation Benchmark for Remote Sensing Vision-Language Models
Karim El Khoury, Maxime Zanella, Christophe De Vleeschouwer +1
Remote Sensing Vision-Language Models (RSVLMs) have shown remarkable potential thanks to large-scale pretraining, achieving strong zero-shot performance on various tasks. However,…
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…