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Contributions on microscopic approaches to solve the train timetabling problem and its integration to the performance of infrastructure maintenance activities. (Contributions d'un modèle microscopique à la résolution du problème deconstruction d'une grille horaire et à la planification des activités demaintenance de l'infrastructure ferroviaire).. Université de Valenciennes et du Hainaut Cambrésis, France, (2016)Timetable rearrangement to cope with railway maintenance activities., , , and . Comput. Oper. Res., (2018)Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing., , , , , , , , , and 4 other author(s). IGARSS, page 5014-5017. IEEE, (2023)Solving the Periodic Timetabling Problem using a Genetic Algorithm., , , and . CoRR, (2014)A Comparative Assessment of Multi-View Fusion Learning For Crop Classification., , , and . IGARSS, page 5631-5634. IEEE, (2023)Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level., , , , , , , , , and 4 other author(s). IGARSS, page 2767-2770. IEEE, (2023)In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data., , and . CoRR, (2024)Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications., , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Influence of Data Cleaning Techniques on Sub-Field Yield Predictions., , , , , , , , , and 5 other author(s). IGARSS, page 4852-4855. IEEE, (2023)Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications., , , and . CoRR, (2023)