| Inferring Dynamic Origin-Destination Flows by Transport Mode using Mobile Phone Data D Bachir, G Khodabandelou, V Gauthier, M EL YACOUBI, J Puchinger Elsevier Journal of Transportation Research Part C, 2019 | 221 | 2019 |
| A fuzzy convolutional attention-based GRU network for human activity recognition G Khodabandelou, H Moon, Y Amirat, S Mohammed Engineering Applications of Artificial Intelligence, 2023 | 70 | 2023 |
| Process mining versus Intention mining G Khodabandelou, C Hug, R Deneckere, C Salinesi Enterprise, Business-Process and Information Systems Modeling, 466-480, 2013 | 65 | 2013 |
| Population Estimation from Mobile Network Traffic Metadata G Khodabandelou, V Gauthier, M El-Yacoubi, M Fiore | 59 | 2016 |
| Estimation of Static and Dynamic Urban Populations with Mobile Network Metadata G Khodabandelou, V Gauthier, M El Yacoubi, M Fiore Journal IEEE Transactions on Mobile Computing, http://doi …, 2018 | 55 | 2018 |
| Attention-Based Gated Recurrent Unit for Gesture Recognition G Khodabandelou, PG Jung, Y Amirat, S Mohammed IEEE Transactions on Automation Science and Engineering Journal, 2020 | 52 | 2020 |
| Supervised intentional process models discovery using hidden markov models G Khodabandelou, C Hug, R Deneckere, C Salinesi IEEE 7th International Conference on Research Challenges in Information …, 2013 | 51 | 2013 |
| Unsupervised discovery of intentional process models from event logs G Khodabandelou, C Hug, R Deneckère, C Salinesi Proceedings of the 11th Working Conference on Mining Software Repositories …, 2014 | 43 | 2014 |
| Link Traffic Speed Forecasting using Convolutional Attention-based Gated Recurrent Unit G Khodabandelou, W Kheriji, F Hadj Selem Applied Intelligence Journal, 10.1007/s10489-020-02020-8, 2020 | 42 | 2020 |
| Supervised vs. unsupervised learning for intentional process model discovery G Khodabandelou, C Hug, R Deneckere, C Salinesi International Workshop on Business Process Modeling, Development and Support …, 2014 | 31 | 2014 |
| Semi-Supervised Generative Adversarial Networks with Temporal Convolutions for Human Activity Recognition H Zilelioglu, G Khodabandelou, A Chibani, Y Amirat IEEE Sensors, 2023 | 29 | 2023 |
| Video-based continuous affect recognition of children with Autism Spectrum Disorder using deep learning M Dia, G Khodabandelou, A Qalid Md Sabri, A Othmani Elsevier Biomedical Signal Processing and Control, 2024 | 27 | 2024 |
| Genome Annotation Across Species using Deep Convolutional Neural Networks G Khodabandelou, E Routhier, J Mozziconacci Journal of PeerJ, 2020 | 27* | 2020 |
| Using Mobile Phone Data Analysis for the Estimation of Daily Urban Dynamics D Bachir, V Gauthier, M El.Yacoubi, G Khodabandelou IEEE Intelligent Transportation Systems Conference, 2017 | 26 | 2017 |
| Fuzzy Neural Network with Support Vector-based Learning for Classification and Regression G Khodabandelou, M Ebadzadeh Journal of Soft Computing, 2019 | 24 | 2019 |
| Combining Bayesian Inference and Clustering for Transport Mode Detection from Sparse and Noisy Geolocation Data D Bachir, G Khodabandelou, V Gauthier, M El ECML/PKDD, 2018 | 23 | 2018 |
| A novel approach to process mining: Intentional process models discovery G Khodabandelou, C Hug, C Salinesi | 23 | 2014 |
| Distributed under Creative Commons CC-BY 4.0 Genome annotation across species using deep convolutional neural networks G Khodabandelou, E Routhier, J Mozziconacci Journal of PeerJ, 2020 | 22* | 2020 |
| Counter-examples generation from a positive unlabeled image dataset F Chiaroni, G Khodabandelou, MC Rahal, N Hueber, F Dufaux Journal of Pattern Recognition, 2020 | 22 | 2020 |
| Intentional process mining: discovering and modeling the goals behind processes using supervised learning R Deneckère, C Hug, G Khodabandelou, C Salinesi International Journal of Information System Modeling and Design 5 (4), 22-47, 2014 | 22 | 2014 |
AmiratProf. Université Paris Est CréteilVerified email at u-pec.fr
