| Deep learning in the biomedical applications: Recent and future status R Zemouri, N Zerhouni, D Racoceanu Applied Sciences 9 (8), 1526, 2019 | 231 | 2019 |
| Recurrent radial basis function network for time-series prediction R Zemouri, D Racoceanu, N Zerhouni Engineering Applications of Artificial Intelligence 16 (5-6), 453-463, 2003 | 177 | 2003 |
| Contribution à la surveillance des systèmes de production à l'aide des réseaux de neurones dynamiques: Application à la e-maintenance R Zemouri Université de Franche-Comté, 2003 | 115 | 2003 |
| Defining and applying prediction performance metrics on a recurrent NARX time series model R Zemouri, R Gouriveau, N Zerhouni Neurocomputing 73 (13-15), 2506-2521, 2010 | 87 | 2010 |
| Deep convolutional variational autoencoder as a 2d-visualization tool for partial discharge source classification in hydrogenerators R Zemouri, M Levesque, N Amyot, C Hudon, O Kokoko, SA Tahan IEEE Access 8, 5438-5454, 2019 | 62 | 2019 |
| A new growing pruning deep learning neural network algorithm (GP-DLNN) R Zemouri, N Omri, F Fnaiech, N Zerhouni, N Fnaiech Neural Computing and Applications 32 (24), 18143-18159, 2020 | 54 | 2020 |
| Features selection procedure for prognostics: An approach based on predictability K Javed, R Gouriveau, R Zemouri, N Zerhouni IFAC Proceedings Volumes 45 (20), 25-30, 2012 | 44 | 2012 |
| Robust, reliable and applicable tool wear monitoring and prognostic: approach based on an improved-extreme learning machine K Javed, R Gouriveau, N Zerhouni, R Zemouri, X Li 2012 IEEE Conference on prognostics and health management, 1-9, 2012 | 42 | 2012 |
| Breast cancer diagnosis based on joint variable selection and constructive deep neural network R Zemouri, N Omri, C Devalland, L Arnould, B Morello, N Zerhouni, ... 2018 IEEE 4th Middle East Conference on Biomedical Engineering (MECBME), 159-164, 2018 | 39 | 2018 |
| Leveraging the power of the combination of CNN and bi-directional LSTM networks for aircraft engine RUL estimation I Remadna, SL Terrissa, R Zemouri, S Ayad, N Zerhouni 2020 Prognostics and Health Management Conference (PHM-Besançon), 116-121, 2020 | 37 | 2020 |
| Constructive deep neural network for breast cancer diagnosis R Zemouri, N Omri, B Morello, C Devalland, L Arnould, N Zerhouni, ... IFAC-PapersOnLine 51 (27), 98-103, 2018 | 36 | 2018 |
| Towards accurate and reproducible predictions for prognostic: An approach combining a RRBF network and an autoRegressive model R Zemouri, R Gouriveau IFAC Proceedings Volumes 43 (3), 140-145, 2010 | 35 | 2010 |
| Prediction of Oncotype DX recurrence score using deep multi-layer perceptrons in estrogen receptor-positive, HER2-negative breast cancer A Baltres, Z Al Masry, R Zemouri, S Valmary-Degano, L Arnould, ... Breast Cancer 27, 1007-1016, 2020 | 34 | 2020 |
| Dimension reduction and 2D-visualization for early change of state detection in a machining process with a variational autoencoder approach A Proteau, R Zemouri, A Tahan, M Thomas The International Journal of Advanced Manufacturing Technology 111, 3597-3611, 2020 | 33 | 2020 |
| Hydrogenerator early fault detection: Sparse dictionary learning jointly with the variational autoencoder R Zemouri, R Ibrahim, A Tahan Engineering Applications of Artificial Intelligence 120, 105859, 2023 | 28 | 2023 |
| Recent research and applications in variational autoencoders for industrial prognosis and health management: A survey R Zemouri, M Lévesque, É Boucher, M Kirouac, F Lafleur, S Bernier, ... 2022 Prognostics and Health Management Conference (PHM-2022 London), 193-203, 2022 | 28 | 2022 |
| Improving data-driven prognostics by assessing predictability of features. K Javed, R Gouriveau, R Zemouri, N Zerhouni Proceedings of the Annual Conference of the Prognostics and Health …, 2011 | 27 | 2011 |
| Predicting the quality of a machined workpiece with a variational autoencoder approach A Proteau, A Tahan, R Zemouri, M Thomas Journal of Intelligent Manufacturing 34 (2), 719-737, 2023 | 25 | 2023 |
| Semi-supervised adversarial variational autoencoder R Zemouri Machine Learning and Knowledge Extraction 2 (3), 20, 2020 | 25 | 2020 |
| Réseaux de neurones récurrents à fonctions de base radiales: RRFR Application au pronostic. RA Zemouri, D Racoceanu, N Zerhouni Rev. d'Intelligence Artif. 16 (3), 307-338, 2002 | 23 | 2002 |
Daniel RACOCEANUSorbonne University, Paris Brain Institute (ICM), Inria team "Aramis"Bestätigte E-Mail-Adresse bei sorbonne-universite.fr
