2023
Scientific journals/Article
- Stassin, S., Corduant, V., MAHMOUDI, S., & Siebert, X. (30 December 2023). Explainability and Evaluation of Vision Transformers: An In-Depth Experimental Study. "Electronics, 13" (1), 175. doi:10.3390/electronics13010175
- Stassin, S., Englebert, A., Nefack, G., Albert, J., Versbraegen, N., Peiffer, G., Doh, M., Riche, N., Frenay, B., & De Vleeschouwer, C. (2023). An Experimental Investigation into the Evaluation of Explainability Methods. "Communications in Computer and Information Science".
Scientific congresses and symposiums/Paper published in a book
- 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.
- Amel, O., Stassin, S., Mahmoudi, S., & Siebert, X. (2023). Multimodal Approach for Harmonized System Code Prediction. In "ESANN 2023 proceedings" (31st). i6doc.com.
- Englebert, A., Stassin, S., Nanfack, G., Mahmoudi, S., Siebert, X., Cornu, O., & De Vleeschouwer, C. (2023). Explaining through Transformer Input Sampling. In "Proceedings of the IEEE/CVF International Conference on Computer Vision". IEEE Xplore. doi:10.1109/ICCVW60793.2023.00088
Scientific conferences in universities or research centers/Scientific conference in universities or research centers
- Stassin, S., Amel, O., Siebert, X., & Mahmoudi, S. (24 May 2023). "Best Approaches for Customs Fraud Detection" [Paper presentation]. Infortech Day.
2022
Scientific congresses and symposiums/Unpublished conference/Abstract
- Stassin, S., Versbraegen, N., Nanfack, G., Jean, E., & Duboquet, F. (September 2022). "Bias Detection On Image Data and their Mitigation on Models" [Paper presentation]. TRAIL Workshop 2022.
- 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.
- Amel, O., Mahmoudi, S., Siebert, X., & Stassin, S. (30 March 2022). "Review of multimodal approaches" [Paper presentation]. Infortech day on Data science, Mons, Belgium.
2021
Parts of books/Contribution to collective works
- Mahmoudi, S., Stassin, S., Daho, M. E. H., Lessage, X., & Mahmoudi, S. (2021). Explainable Deep Learning for Covid-19 Detection Using Chest X-ray and CT-Scan Images. In "Intelligent Healthcare Informatics for Fighting the COVID-19 and Other Pandemics and Epidemics" (pp. 323-338). Springer.
- Mahmoudi, S., Stassin, S., Daho, M. E. H., Lessage, X., & Mahmoudi, S. (2021). Explainable Deep Learning for Covid-19 detection using chest X-ray and CT images. In "Intelligent Healthcare Informatics for Fighting the COVID-19 and Other Pandemics and Epidemics". Springer. doi:10.1007/978-3-030-72752-9_16