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ORCIDTristan Gomez
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2020 – today
- 2023
[i5]Tristan Gomez, Harold Mouchère:
Enhancing Post-Hoc Explanation Benchmark Reliability for Image Classification. CoRR abs/2311.17876 (2023)- 2022
- [b1]Tristan Gomez:
Attention spatiale artificielle pour des modèles profonds interprétables de qualité embryonnaire. (Artificial spatial attention for interpretable deep models of embryonic quality). Nantes University, France, 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) - [c2]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 - [c1]Tristan Gomez, Thomas Fréour, Harold Mouchère:
Metrics for Saliency Map Evaluation of Deep Learning Explanation Methods. ICPRAI (1) 2022: 84-95 - [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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