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pro vyhledávání: '"Zanella, Maxime"'
The development of vision-language models (VLMs) for histo-pathology has shown promising new usages and zero-shot performances. However, current approaches, which decompose large slides into smaller patches, focus solely on inductive classification,
Externí odkaz:
http://arxiv.org/abs/2409.01883
Autor:
Khoury, Karim El, Zanella, Maxime, Gérin, Benoît, Godelaine, Tiffanie, Macq, Benoît, Mahmoudi, Saïd, De Vleeschouwer, Christophe, Ayed, Ismail Ben
Vision-Language Models for remote sensing have shown promising uses thanks to their extensive pretraining. However, their conventional usage in zero-shot scene classification methods still involves dividing large images into patches and making indepe
Externí odkaz:
http://arxiv.org/abs/2409.00698
Transduction is a powerful paradigm that leverages the structure of unlabeled data to boost predictive accuracy. We present TransCLIP, a novel and computationally efficient transductive approach designed for Vision-Language Models (VLMs). TransCLIP i
Externí odkaz:
http://arxiv.org/abs/2406.01837
Autor:
Zanella, Maxime, Ayed, Ismail Ben
Recent progress in the few-shot adaptation of Vision-Language Models (VLMs) has further pushed their generalization capabilities, at the expense of just a few labeled samples within the target downstream task. However, this promising, already quite a
Externí odkaz:
http://arxiv.org/abs/2405.18541
Autor:
Zanella, Maxime, Ayed, Ismail Ben
The development of large vision-language models, notably CLIP, has catalyzed research into effective adaptation techniques, with a particular focus on soft prompt tuning. Conjointly, test-time augmentation, which utilizes multiple augmented views of
Externí odkaz:
http://arxiv.org/abs/2405.02266
Autor:
Piérard, Sébastien, Cioppa, Anthony, Halin, Anaïs, Vandeghen, Renaud, Zanella, Maxime, Macq, Benoît, Mahmoudi, Saïd, Van Droogenbroeck, Marc
Various tasks encountered in real-world surveillance can be addressed by determining posteriors (e.g. by Bayesian inference or machine learning), based on which critical decisions must be taken. However, the surveillance domain (acquisition device, o
Externí odkaz:
http://arxiv.org/abs/2211.10119