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Miriam Doh
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2020 – today
- 2024
- [c3]Miriam Doh, Anastasia Karagianni:
"My Kind of Woman": Analysing Gender Stereotypes in AI through The Averageness Theory and EU Law. HHAI Workshops 2024: 114-131 - [c2]Miriam Doh
, Corinna Canali
Pixels of Perfection and Self-Perception: Deconstructing AR Beauty Filters and Their Challenge to Unbiased Body Image. IMX 2024: 349-353 - [i4]Miriam Doh, Caroline Mazini Rodrigues, Nicolas Boutry, Laurent Najman, Matei Mancas, Hugues Bersini:
Bridging Human Concepts and Computer Vision for Explainable Face Verification. CoRR abs/2403.08789 (2024) - [i3]Miriam Doh, Anastasia Karagianni:
"My Kind of Woman": Analysing Gender Stereotypes in AI through The Averageness Theory and EU Law. CoRR abs/2407.17474 (2024) - [i2]Julien Albert, Martin Balfroid, Miriam Doh, Jérémie Bogaert, Luca La Fisca, Liesbet De Vos, Bryan Renard, Vincent Stragier, Emmanuel Jean:
User Preferences for Large Language Model versus Template-Based Explanations of Movie Recommendations: A Pilot Study. CoRR abs/2409.06297 (2024) - 2023
- [c1]Miriam Doh, Caroline Mazini Rodrigues, Nicolas Boutry, Laurent Najman, Matei Mancas, Hugues Bersini:
Bridging Human Concepts and Computer Vision for Explainable Face Verification. BEWARE@AI*IA 2023: 15-29 - [i1]Sédrick Stassin, Alexandre Englebert, Géraldin Nanfack, Julien Albert, Nassim Versbraegen, Gilles Peiffer, Miriam Doh, Nicolas Riche, Benoît Frénay, Christophe De Vleeschouwer:
An Experimental Investigation into the Evaluation of Explainability Methods. CoRR abs/2305.16361 (2023)
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last updated on 2024-11-25 22:48 CET by the dblp team
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