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Gloesener Maxime

Université de Mons - UMONS > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle

Main Referenced Co-authors
BENKEDADRA, Mohamed  (2)
MAHMOUDI, Sidi  (2)
LERAT, Jean-Sébastien  (1)
Main Referenced Keywords
CNN Networks (1); Deep Learning (1); Edge AI (1); Edge AI, XAI, Deep Learning (1); Forest Fire Detection (1);
Main Referenced Disciplines
Computer science (2)

Publications (total 2)

The most downloaded
4 downloads
Mahmoudi, S., Gloesener, M., Benkedadra, M., & Lerat, J.-S. (2025). Edge AI System for Real-Time and Explainable Forest Fire Detection Using Compressed Deep Learning Models. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3, 847-854. doi:10.5220/0013382500003912 https://hdl.handle.net/20.500.12907/51915

The most cited

1 citations (OpenAlex)

Mahmoudi, S., Gloesener, M., Benkedadra, M., & Lerat, J.-S. (2025). Edge AI System for Real-Time and Explainable Forest Fire Detection Using Compressed Deep Learning Models. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3, 847-854. doi:10.5220/0013382500003912 https://hdl.handle.net/20.500.12907/51915

Mahmoudi, S., Gloesener, M., Benkedadra, M., & Lerat, J.-S. (2025). Edge AI System for Real-Time and Explainable Forest Fire Detection Using Compressed Deep Learning Models. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3, 847-854. doi:10.5220/0013382500003912
Peer reviewed

Mahmoudi, S., Gloesener, M., & Benkedadra, M. (2025). Edge AI for securing railway stations and construction sites [Paper presentation]. Hannover Messe, Hannover, Germany.

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