| Learning More Universal Representations for Transfer-Learning Y Tamaazousti, HL Borgne, C Hudelot, MEA Seddik, M Tamaazousti IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 | 54 | 2019 |
| How to Make a Pizza: Learning a Compositional Layer-Based GAN Model DP Papadopoulos, Y Tamaazousti, F Ofli, I Weber, A Torralba IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 22 | 2019 |
| MuCaLe-Net: Multi Categorical-Level Networks to Generate More Discriminating Features Y Tamaazousti, H Le Borgne, C Hudelot IEEE Computer Vision and Pattern Recognition (CVPR), 2017 | 20 | 2017 |
| AMECON: Abstract Meta-Concept Features for Text-Illustration I Chami, Y Tamaazousti, H Le Borgne ACM International Conference on Multimedia Retrieval (ICMR), 2017 | 13 | 2017 |
| Deep Multi-class Adversarial Specularity Removal J Lin, M El Amine Seddik, M Tamaazousti, Y Tamaazousti, A Bartoli Scandinavian Conference on Image Analysis (SCIA), 2019 | 11 | 2019 |
| Joint Learning of Pre-Trained and Random Units for Domain Adaptation in Part-of-Speech Tagging S Meftah, Y Tamaazousti, N Semmar, H Essafi, F Sadat North American Chapter of ACL: Human Language Technologies (NAACL-HLT), 2019 | 11 | 2019 |
| Diverse Concept-Level Features for Multi-Object Classification Y Tamaazousti, H Le Borgne, C Hudelot ACM International Conference on Multimedia Retrieval (ICMR), 2016 | 10 | 2016 |
| Multi-Task Supervised Pretraining for Neural Domain Adaptation S Meftah, N Semmar, MA Tahiri, Y Tamaazousti, H Essafi, S Fatiha SocialNLP Workshop at ACL, 2020 | 9 | 2020 |
| Vision-Language Integration using Constrained Local Semantic Features Y Tamaazousti, H Le Borgne, A Popescu, E Gadeski, A Ginsca, C Hudelot Journal of Computer Vision and Image Understanding (CVIU), 2017 | 9 | 2017 |
| Constrained Local Enhancement of Semantic Features by Content-Based Sparsity Y Tamaazousti, H Le Borgne, A Popescu ACM International Conference on Multimedia Retrieval (ICMR), 2016 | 9 | 2016 |
| On The Universality of Visual and Multimodal Representations Y Tamaazousti Ph.D. Thesis - CentraleSupélec (University of Paris-Saclay), 2018 | 7 | 2018 |
| Supervised Learning of Entity Disambiguation Models by Negative Sample Selection H Daher, R Besançon, O Ferret, H Le Borgne, AL Daquo, Y Tamaazousti International Conference on Computational Linguistics and Intelligent Text …, 2017 | 6 | 2017 |
| Image Annotation and Two Paths to Text Illustration H Le Borgne, E Gadeski, I Chami, TQN Tran, Y Tamaazousti, AL Ginsca, ... ImageCLEF 2016 Evaluation Labs and Workshop, Online Working Notes, 2016 | 4 | 2016 |
| Learning Finer-class Networks for Universal Representations J Girard, Y Tamaazousti, HL Borgne, C Hudelot British Machine Vision Conference (BMVC), 2018 | 3 | 2018 |
| Agrégation de descripteurs sémantiques locaux contraints par parcimonie basée sur le contenu Y Tamaazousti, H Le Borgne, A Popescu Reconnaissance des formes et intelligence artificielle (RFIA), 2016 | 3 | 2016 |
| On the hidden negative transfer in sequential transfer learning for domain adaptation from news to tweets S Meftah, N Semmar, Y Tamaazousti, H Essafi, F Sadat Proceedings of the Second Workshop on Domain Adaptation for NLP, 140-145, 2021 | 2 | 2021 |
| Where is the Fake? Patch-Wise Supervised GANs for Texture Inpainting A Ben Saad, Y Tamaazousti, J Kherroubi, A He IEEE International Conference on Image Processing (ICIP), 2020 | 2 | 2020 |
| Désambiguïsation d’entités nommées par apprentissage de modèles d’entités à large échelle H Daher, R Besançon, O Ferret, H Le Borgne, AL Daquo, Y Tamaazousti CORIA, 2017 | 2 | 2017 |
| Descripteurs à divers niveaux de concepts pour la classification d’images multi-objets Y Tamaazousti, H Le Borgne, C Hudelot Reconnaissance des formes et intelligence artificielle (RFIA), 2016 | 2 | 2016 |
| Neural supervised domain adaptation by augmenting pre-trained models with random units S Meftah, N Semmar, Y Tamaazousti, H Essafi, F Sadat arXiv preprint arXiv:2106.04935, 2021 | 1 | 2021 |
Hervé Le BorgneCEA List, FranceVerified email at cea.fr
