Profil

Ennadifi Elias

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

ORCID
0000-0002-3000-4956
Main Referenced Co-authors
GOSSELIN, Bernard  (8)
Carlier, Alexis (4)
Dandrifosse, Sébastien (4)
Laraba, Sohaib  (4)
Mercatoris, Benoît (4)
Main Referenced Keywords
counting (3); YOLOv5 (3); Deep Learning (2); DeepMAC (2); Detection (2);
Main Referenced Disciplines
Computer science (6)
Electrical & electronics engineering (2)

Publications (total 8)

The most downloaded
15 downloads
Mokhtari, M. E. A., Mancas, M., Vandenbulcke, V., Ennadifi, E., Laraba, S., Tazir, M., & Gosselin, B. (2023). Efficient Action Recognition for Drones: A Comparative Study of Lightweight and Traditional Models [Paper presentation]. European Test and Telemetry Conference, Toulouse, France. https://hdl.handle.net/20.500.12907/46053

The most cited

14 citations (Scopus®)

Dandrifosse, S.* , Ennadifi, E.* , Carlier, A., Gosselin, B., Dumont, B., & Mercatoris, B. (2022). Deep Learning for Wheat Ear Segmentation and Ear Density Measurement: From Heading to Maturity. Computers and Electronics in Agriculture. https://hdl.handle.net/20.500.12907/43085

Ennadifi, E., Ravet, T., Mancas, M., Mokhtari, M. E. A., & Gosselin, B. (2023). Enhancing VR Gaming Experience using Computational Attention Models and Eye-Tracking. ACM International Conference on Interactive Media Experiences (IMX).
Peer reviewed

Mokhtari, M. E. A., Mancas, M., Vandenbulcke, V., Ennadifi, E., Laraba, S., Tazir, M., & Gosselin, B. (2023). Efficient Action Recognition for Drones: A Comparative Study of Lightweight and Traditional Models [Paper presentation]. European Test and Telemetry Conference, Toulouse, France.

Mokhtari, M. E. A., Vandenbulcke, V., Laraba, S., Mancas, M., Ennadifi, E., Tazir, M., & Gosselin, B. (2022). Semi-synthetic Data for Automatic Drone Shadow Detection. ESANN.
Peer reviewed

Ennadifi, E., Dandrifosse, S., Mokhtari, M. E. A., Carlier, A., Laraba, S., Mercatoris, B., & Gosselin, B. (2022). Local Unsupervised Wheat Head Segmentation. ICCP 2022.
Peer reviewed

Dandrifosse, S.* , Ennadifi, E.* , Carlier, A., Gosselin, B., Dumont, B., & Mercatoris, B. (2022). Contrasted-Fertilization Wheat Ear Dataset 2020. doi:10.5281/zenodo.5709821
* These authors have contributed equally to this work.

Dandrifosse, S.* , Ennadifi, E.* , Carlier, A., Gosselin, B., Dumont, B., & Mercatoris, B. (2022). Deep Learning for Wheat Ear Segmentation and Ear Density Measurement: From Heading to Maturity. Computers and Electronics in Agriculture.
Peer Reviewed verified by ORBi
* These authors have contributed equally to this work.

Dandrifosse, S., Ennadifi, E., Carlier, A., Gosselin, B., Dumont, B., & Mercatoris, B. (2022). Effect of the sun on the measurement of wheat ear density by deep learning. The 15th International Conference on Precision Agriculture.
Peer reviewed

Ennadifi, E., Laraba, S., Vincke, D., Mercatoris, B., & Gosselin, B. (2020). Wheat Diseases Classification and Localization Using Convolutional Neural Networks and GradCAM Visualization. IEEE ISCV2020.
Peer reviewed

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