 | Monter d'un niveau |
Kruse, J., Ciechanowski, L., Dupuis, A., & Gloor, P. A. (2024). Leveraging the sensitivity of plants with deep learning to recognize human emotions. Sensors, 24(6), 1917 (22 pages). Disponible
Dupuis, A., Dadouchi, C., & Agard, B. (2023). Methodology for multi-temporal prediction of crop rotations using recurrent neural networks. Smart Agricultural Technology, 4, 100152 (13 pages). Disponible
Dupuis, A., Dadouchi, C., & Agard, B. (2023). Performances of a Seq2Seq-LSTM methodology to predict crop rotations in Québec. Smart Agricultural Technology, 4, 100180 (12 pages). Disponible
Dupuis, A., Dadouchi, C., & Agard, B. (2023). A decision support system for sequencing production in the manufacturing industry. Computers & Industrial Engineering, 185, 109686 (14 pages). Lien externe
Dupuis, A., Dadouchi, C., Agard, B., & Pellerin, R. (novembre 2022). Forecasting future product sequences to be processed in tire production using deep learning technique [Communication écrite]. International Conference on ENTERprise Information Systems (CENTERIS 2022), Lisbon, Portugal. Publié dans Procedia Computer Science, 219. Lien externe
Dupuis, A., Dadouchi, C., & Agard, B. (juin 2023). Technologies numériques et émotions : spectre d'analyse du comportement décisionnel des travailleurs [Communication écrite]. CIGI Qualita MOSIM 2023, Trois-Rivières, Qc, Canada (7 pages). Lien externe
Dupuis, A., Dadouchi, C., & Agard, B. (2022). Predicting crop rotations using process mining techniques and Markov principals. Computers and Electronics in Agriculture, 194, 106686 (16 pages). Lien externe
