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Hubens Nathan

Université de Mons - UMONS > Faculté Polytechnique > Service Information, Signal et Intelligence artificielle

Main Referenced Co-authors
GOSSELIN, Bernard  (7)
MANCAS, Matei  (7)
Preda, Marius (7)
Zaharia, Titus (7)
DUTOIT, Thierry  (4)
Main Referenced Keywords
Computer Networks and Communications (2); Communication (1); Computer Science (all) (1); Computer Science - Computer Vision and Pattern Recognition (1); Computer Science - Information Retrieval (1);
Main Referenced Unit & Research Centers
CRTI - Centre de Recherche en Technologie de l'Information (5)
Main Referenced Disciplines
Computer science (9)
Library & information sciences (2)
Electrical & electronics engineering (1)

Publications (total 12)

The most downloaded
80 downloads
Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2021). Fake-Buster: A Lightweight Solution for Deepfake Detection. Proceedings of SPIE: The International Society for Optical Engineering. doi:10.1117/12.2596317 https://hdl.handle.net/20.500.12907/42438

The most cited

4 citations (OpenAlex)

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2022). One-Cycle Pruning: Pruning Convnets With Tight Training Budget. 2022 IEEE International Conference on Image Processing (ICIP). doi:10.1109/icip46576.2022.9897980 https://hdl.handle.net/20.500.12907/44228

Seddati, O., Hubens, N., Dupont, S., & Dutoit, T. (2023). A Recipe for Efficient SBIR Models: Combining Relative Triplet Loss with Batch Normalization and Knowledge Distillation. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/48304.

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (November 2022). FasterAI: A Lightweight Library for Neural Networks Compression. Electronics, 11 (22), 3789. doi:10.3390/electronics11223789
Peer Reviewed verified by ORBi

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2022). One-Cycle Pruning: Pruning Convnets With Tight Training Budget. 2022 IEEE International Conference on Image Processing (ICIP). doi:10.1109/icip46576.2022.9897980
Peer reviewed

Delvigne, V., Tits, N., La Fisca, L., Hubens, N., Maiorca, A., Wannous, H., Dutoit, T., & Vandeborre, J.-P. (March 2022). Where Is My Mind (Looking at)? A Study of the EEG–Visual Attention Relationship. Informatics, 9 (1), 26. doi:10.3390/informatics9010026
Peer Reviewed verified by ORBi

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2022). Improve Convolutional Neural Network Pruning by Maximizing Filter Variety. In S. Sclaroff (Ed.), Image Analysis and Processing – ICIAP 2022 - 21st International Conference, 2022, Proceedings. Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-06427-2_32
Peer reviewed

Maiorca, A., Hubens, N., Laraba, S., & Dutoit, T. (2022). Towards Lightweight Neural Animation : Exploration of Neural Network Pruning in Mixture of Experts-based Animation Models. Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP). doi:10.5220/0010908700003124
Peer reviewed

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (25 November 2021). Introduction to Compression Techniques for Lighter Neural Networks [Paper presentation]. Workshop Energy4Climate, Paris, France.
Peer reviewed

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2021). Fake-Buster: A Lightweight Solution for Deepfake Detection. Proceedings of SPIE: The International Society for Optical Engineering. doi:10.1117/12.2596317
Peer reviewed

Hubens, N., Mancas, M., Gosselin, B., Preda, M., & Zaharia, T. (2021). One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget [Paper presentation]. Sparsity in Neural Networks: Advancing Understanding and Practice, Remote, NULL.

Hubens, N., Mancas, M., Gosselin, B., Decombas, M., Preda, M., Zaharia, T., & Dutoit, T. (2020). An Experimental Study of the Impact of Pre-Training on the Pruning of a Convolutional Neural Network [Paper presentation]. APPIS 2020: Proceedings of the 3rd International Conference on Applications of Intelligent Systems, Las Palmas de Gran Canaria, Spain.

Delbrouck, J.-B., Maiorca, A., Hubens, N., & Dupont, S. (2019). Modulated Self-attention Convolutional Network for VQA. In NeurIPS 2019 Workshop on Visually-Grounded Interaction and Language (ViGIL) (2019). -.
Peer reviewed

Hubens, N. (20 September 2019). Towards smaller and faster DNNs [Paper presentation]. Machine Learning Workshop, Paris, France.

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