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2020 – today
- 2024
[c4]Chloe He
, Neringa Karpaviciute, Rishabh Hariharan, Céline Jacques, Jérôme Chambost, Jonas Malmsten, Nikica Zaninovic, Koen Wouters, Thomas Fréour, Cristina Hickman, Francisco Vasconcelos:
Embryo Graphs: Predicting Human Embryo Viability from 3D Morphology. MICCAI (4) 2024: 80-90- 2022
- [j1]Tristan Gomez, Suiyi Ling, Thomas Fréour, Harold Mouchère:
BR-NPA: A non-parametric high-resolution attention model to improve the interpretability of attention. Pattern Recognit. 132: 108927 (2022) - [c3]Tristan Gomez, Thomas Fréour, Harold Mouchère:
Comparison of Attention Models and Post-hoc Explanation Methods for Embryo Stage Identification: A Case Study. ICPR Workshops (3) 2022: 216-230 - [c2]Tristan Gomez, Thomas Fréour, Harold Mouchère:
Metrics for Saliency Map Evaluation of Deep Learning Explanation Methods. ICPRAI (1) 2022: 84-95 - [c1]Chloe He, Céline Jacques, Jérôme Chambost, Jonas Malmsten, Koen Wouters, Thomas Fréour, Nikica Zaninovic, Cristina Hickman, Francisco Vasconcelos:
Super-Focus: Domain Adaptation for Embryo Imaging via Self-supervised Focal Plane Regression. MICCAI (2) 2022: 732-742 - [i4]Tristan Gomez, Thomas Fréour, Harold Mouchère:
Metrics for saliency map evaluation of deep learning explanation methods. CoRR abs/2201.13291 (2022) - [i3]Tristan Gomez, Magalie Feyeux, Nicolas Normand, Laurent David, Perrine Paul-Gilloteaux, Thomas Fréour, Harold Mouchère:
Towards deep learning-powered IVF: A large public benchmark for morphokinetic parameter prediction. CoRR abs/2203.00531 (2022) - [i2]Tristan Gomez, Thomas Fréour, Harold Mouchère:
Comparison of attention models and post-hoc explanation methods for embryo stage identification: a case study. CoRR abs/2205.06546 (2022) - 2021
- [i1]Tristan Gomez, Suiyi Ling, Thomas Fréour, Harold Mouchère:
Improve the Interpretability of Attention: A Fast, Accurate, and Interpretable High-Resolution Attention Model. CoRR abs/2106.02566 (2021)
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