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Valentine Wargnier-Dauchelle
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2020 – today
- 2023
- [b1]Valentine Wargnier-Dauchelle:
Interprétabilité des réseaux de neurones profonds et segmentation faiblement supervisée des lésions cérébrales sur IRM. (Deep neural networks interpretability and weakly supervised segmentation of brain lesions on MRI). INSA de Lyon, France, 2023 - [j1]Valentine Wargnier-Dauchelle
, Thomas Grenier
, Françoise Durand-Dubief
, François Cotton
, Michaël Sdika
:
A Weakly Supervised Gradient Attribution Constraint for Interpretable Classification and Anomaly Detection. IEEE Trans. Medical Imaging 42(11): 3336-3347 (2023) - [c5]Morgane Des Ligneris, Axel Bonnet, Yohan Chatelain, Tristan Glatard, Michaël Sdika, Gaël Vila, Valentine Wargnier-Dauchelle, Sorina Camarasu-Pop, Carole Frindel:
Reproducibility of Tumor Segmentation Outcomes with a Deep Learning Model. ISBI 2023: 1-5 - [c4]Slim Hachicha, Célia Le, Valentine Wargnier-Dauchelle, Michaël Sdika:
Robust Unsupervised Image to Template Registration Without Image Similarity Loss. MILLanD@MICCAI 2023: 148-157 - 2021
- [c3]Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika:
A More Interpretable Classifier For Multiple Sclerosis. ISBI 2021: 1062-1066 - 2020
- [c2]Valentine Wargnier-Dauchelle, Camille Simon Chane, Aymeric Histace:
Saliency Maps of Video-colonoscopy Images for the Analysis of Their Content and the Prevention of Colorectal Cancer Risks. BIOSIGNALS 2020: 106-114
2010 – 2019
- 2019
- [c1]Valentine Wargnier-Dauchelle, Camille Simon Chane, Aymeric Histace:
Retinal Blood Vessels Segmentation: Improving State-of-the-Art Deep Methods. CAIP Workshops 2019: 5-16
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