Profil

Lerat Jean-Sébastien

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

ORCID
0000-0003-4468-0899
Main Referenced Co-authors
MAHMOUDI, Sidi  (10)
MAHMOUDI, Saïd  (6)
Lenaerts, Tom (2)
BENKEDADRA, Mohamed  (1)
Faust, Karoline (1)
Main Referenced Keywords
deep learning (2); high performance computing (2); 16S rDNA sequencing (1); cloud computing (1); CNN Networks (1);
Main Referenced Disciplines
Computer science (11)
Zoology (1)
Library & information sciences (1)

Publications (total 12)

The most downloaded
112 downloads
Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (2022). Distributed Deep Learning: From Single-Node to Multi-Node Architecture. Electronics. doi:10.3390/electronics11101525 https://hdl.handle.net/20.500.12907/42655

The most cited

177 citations (OpenAlex)

Faust, K., Lima-Mendez, G., Lerat, J.-S., Sathirapongsasuti, J. F., Knight, R., Huttenhower, C., Lenaerts, T., & Raes, J. (2015). Cross-biome comparison of microbial association networks. Frontiers in Microbiology. doi:10.3389/fmicb.2015.01200 https://hdl.handle.net/20.500.12907/876

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

Lerat, J.-S., & Mahmoudi, S. (2025). Scalable Deep Learning for Industry 4.0: Speedup with Distributed Deep Learning and Environmental Sustainability Considerations. In Lecture Notes in Networks and Systems. Switzerland: Springer Nature Switzerland. doi:10.1007/978-3-031-78698-3_10
Peer reviewed

Lerat, J.-S., & Mahmoudi, S. (2023). Scalable Deep Learning for Industry 4.0: Speedup with Distributed Deep Learning and Environmental Sustainability Considerations. 2023 IEEE 6th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech). doi:10.1007/978-3-031-78698-3_10
Peer reviewed

Lerat, J.-S., & Mahmoudi, S. (2023). Architecture to Distribute Deep Learning Models on Containers and Virtual Machines for Industry 4.0*. IEEE Cloud Computing. doi:10.1109/cloudtech58737.2023.10366111
Peer Reviewed verified by ORBi

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (2023). Single Node Deep Learning Frameworks: Comparative study and CPU/GPU performance analysis. Concurrency and Computation: Practice and Experience.
Peer Reviewed verified by ORBi

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (06 September 2022). Apprentissage profond distribué : d’un seul nœud vers plusieurs nœuds de calcul [Poster presentation]. Mardi des chercheurs, Mons, Belgium.

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (2022). Distributed Deep Learning: From Single-Node to Multi-Node Architecture. Electronics. doi:10.3390/electronics11101525
Peer Reviewed verified by ORBi

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (22 November 2021). Single node deep learning frameworks: Comparative study and CPU/GPU performance analysis. Concurrency and Computation: Practice and Experience, 35 (14).
Peer Reviewed verified by ORBi

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (27 July 2021). Deep Learning Frameworks: Performances Analysis [Paper presentation]. DeepLearn, Las Palmas de Gran Canaria, Spain.

Lerat, J.-S., Mahmoudi, S., & Mahmoudi, S. (30 March 2021). Comparaison des frameworks d'apprentissage profond sur un seul noeud de calcul [Poster presentation]. Mardi des Chercheurs, Virtual Meeting, Unknown/unspecified.

Faust, K., Lima-Mendez, G., Lerat, J.-S., Sathirapongsasuti, J. F., Knight, R., Huttenhower, C., Lenaerts, T., & Raes, J. (2015). Cross-biome comparison of microbial association networks. Frontiers in Microbiology. doi:10.3389/fmicb.2015.01200
Peer Reviewed verified by ORBi

Lerat, J.-S., Han, T. A., & Lenaerts, T. (2013). Evolution of common-pool resources and social welfare in structured populations [Paper presentation]. International Joint Conference on Artificial Intelligence, Beijing, China.

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