5 papers · 1 filter
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…
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…
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,…
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…
Physically Interpretable Probabilistic Domain Characterization
Anaïs Halin, Sébastien Piérard, Renaud Vandeghen +10
Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when fac…