Ouardirhi, Z.* , Amel, O., Zbakh, M., & Mahmoudi, S. (28 February 2024). FuDensityNet: Fusion-Based Density-Enhanced Network for Occlusion Handling [Paper presentation]. VISAPP 2024, Rome, Italy. |
Stassin, S., Amel, O., Siebert, X., & Mahmoudi, S. (24 May 2023). Best Approaches for Customs Fraud Detection [Paper presentation]. Infortech Day. |
Mahmoudi, S., Amel, O., Stassin, S., Liagre, M., Benkedadra, M., & Mancas, M. (May 2023). A Review and Comparative Study of Explainable Deep Learning Models Applied on Action Recognition in Real Time. Electronics, 12 (9), 2027. doi:10.3390/electronics12092027 Peer Reviewed verified by ORBi |
Stassin, S., Amel, O., Mahmoudi, S., & Siebert, X. (2023). Similarity versus Supervision: Best Approaches for HS Code Prediction. In ESANN 2023 proceedings (31st). i6doc.com. Peer reviewed |
Amel, O., Stassin, S., Mahmoudi, S., & Siebert, X. (2023). Multimodal Approach for Harmonized System Code Prediction. In ESANN 2023 proceedings (31st). i6doc.com. Peer reviewed |
Amel, O., Mahmoudi, S., Siebert, X., & Hadjila fethallah. (24 August 2022). Multimodal learning for action recognition and customs fraud detection [Poster presentation]. deep learning indaba 2022, Tunis, Tunisia. Editorial reviewed |
Amel, O., Mahmoudi, S., & Siebert, X. (28 July 2022). Multimodal learning for customs fraud detection and action recognition [Paper presentation]. Deeplearn summer school 2022. Editorial reviewed |
Stassin, S.* , Amel, O., Mahmoudi, S., & Siebert, X. (30 March 2022). Artificial Intelligence and Natural Language Processing for Customs Fraud Prediction [Paper presentation]. InforTech Day, Mons, Belgium. Editorial reviewed |
Amel, O., Mahmoudi, S., Siebert, X., & Stassin, S. (30 March 2022). Review of multimodal approaches [Paper presentation]. Infortech day on Data science, Mons, Belgium. |