Teaching
Courses
- INF 1220 - Introduction à la programmation
- INF 1420 - Interfaces humain-machine
- INF 1421 - Apprentissage machine
- INF 1427 - Architecture des ordinateurs
- INF 1428 - Théorie des langages et des automates
- INF 1429 - Systèmes d'exploitation
- INF 6409 - Forage de données
- SCI 1017 - Traitement des données massives
Course under preparation
- SCI 1060 - Apprentissage par Renforcement
Publications & Presentations
This section shows the documents (if any) that are available in R-libre, TELUQ's open access research publication repository.
Journal articles (refereed)
Jemal, Imene; Abou-Abbas, Lina; Henni, Khadidja; Mitiche, Amar, & Mezghani, Neila (2024). Domain adaptation for EEG-based, cross-subject epileptic seizure prediction. Frontiers in Neuroinformatics, 18, 1303380. https://doi.org/10.3389/fninf.2024.1303380
Abou-Abbas, Lina; Henni, Khadidja; Jemal, Imene; Mitiche, Amar, & Mezghani, Neila (2023). Patient-independent epileptic seizure detection by stable feature selection. Expert Systems with Applications, 232, 120585. https://doi.org/10.1016/j.eswa.2023.120585
Abou-Abbas, Lina; Jemal, Imene; Henni, Khadidja; Ouakrim, Youssef; Mitiche, Amar, & Mezghani, Neila (2022). EEG oscillatory power and complexity for epileptic seizure detection. Applied Sciences, 12 (9), 4181. https://doi.org/10.3390/app12094181
Henni, Khadidja; Mezghani, Neila, & Mitiche, Amar (2020). Cluster density properties define a graph for effective pattern feature selection. IEEE Access, 8, 62841-62854. https://doi.org/10.1109/ACCESS.2020.2981265
Henni, Khadidja; Mezghani, Neila, & Gouin-Vallerand, Charles (2018). Unsupervised graph-based feature selection via subspace and pagerank centrality. Expert Systems with Applications, 114, 46-53. doi: 10.1016/j.eswa.2018.07.029
Henni, Khadidja; Mezghani, Neila; Gouin-Vallerand, Charles; Ruer, Perrine; Ouakrim, Youssef, & Vallières, Évelyne F. (2018). Feature selection for driving fatigue characterization and detection using visual- and signal-based sensors. Applied Informatics, 5 (7), 1-15. https://doi.org/10.1186/s40535‑018‑0054‑9
Papers in conference proceedings (refereed)
Jemal, Imene; Mitiche, Amar; Abou-Abbas, Lina; Henni, Khadidja, & Mezghani, Neila (2021). An effective deep neural network architecture for cross-subject epileptic seizure detection in EEG data. In Proceedings of CECNet 2021: The 11th International Conference on Electronics, Communications and Networks (CECNet). IOS Press. https://doi.org/10.3233/FAIA210389
Abou-Abbas, Lina; Jemal, Imene; Henni, Khadidja; Mitiche, Amar, & Mezghani, Neila (2021). Focal and generalized seizures distinction by rebalancing class data and random forest classification. In Bioengineering and Biomedical Signal and Image Processing, vol. 12940 (p. 63-70). Springer. ISBN 978-3-030-88163-4 https://doi.org/10.1007/978-3-030-88163-4_6
Zgolli, Fatma; Henni, Khadidja; Haddad, Rim; Mitiche, Amar; Ouakrim, Youssef; Hagemeister, Nicola; Venditolli, Pascal-André; Fuentes, Alexandre, & Mezghani, Neila (2018). Kinematic data clustering for healthy knee gait characterization. In Proceedings of the Second Annual IEEE Life Sciences Conference (LSC 2018) (p. 239-242). IEEE. ISBN 978-1-5386-6709-5 https://doi.org/10.1109/LSC.2018.8572119
Henni, Khadidja; Mezghani, Neila; Gouin-Vallerand, Charles; Ruer, Perrine, & Vallières, Évelyne F. (2018). Driving Fatigue Characterization using Feature Ranking. In 9th International Symposium on Signal, Image, Video and Communications (ISIVC) (p. 209-214). IEEE. ISBN 978-1-5386-8174-9 https://doi.org/10.1109/ISIVC.2018.8709179