Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ikram Chraibi Kaadoud"'
Autor:
Masrour Makaremi, Alireza Vafaei Sadr, Benoit Marcy, Ikram Chraibi Kaadoud, Ali Mohammad-Djafari, Salomé Sadoun, François De Brondeau, Bernard N’kaoua
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract Mandibular retrognathia (C2Rm) is one of the most common oral pathologies. Acquiring a better understanding of the points of impact of C2Rm on the entire skull is of major interest in the diagnosis, treatment, and management of this dysmorph
Externí odkaz:
https://doaj.org/article/8f2262b094c24acabf59a2f65b548ec9
Publikováno v:
Frontiers in Psychiatry, Vol 12 (2021)
Artificial intelligence (AI) algorithms together with advances in data storage have recently made it possible to better characterize, predict, prevent, and treat a range of psychiatric illnesses. Amid the rapidly growing number of biological devices
Externí odkaz:
https://doaj.org/article/42f4feac1f244430834da16f5d886664
Autor:
Ikram Chraibi Kaadoud, Adrien Bennetot, Barbara Mawhin, Vicky Charisi, Natalia Díaz-Rodríguez
Publikováno v:
Neural Networks. 155:95-118
During the learning process, a child develops a mental representation of the task he or she is learning. A Machine Learning algorithm develops also a latent representation of the task it learns. We investigate the development of the knowledge constru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f33a69e6333b71e58550a8aaa7fa50f
https://doi.org/10.1016/j.neunet.2022.08.002
https://doi.org/10.1016/j.neunet.2022.08.002
Publikováno v:
Revue d'Orthopédie Dento-Faciale. 56:159-162
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e20bd1dff9eade90392b67f2a7ed1bfe
https://doi.org/10.1051/odf/2022017
https://doi.org/10.1051/odf/2022017
Publikováno v:
L’Orthodontie Française. 93:31-34
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd0969792c876c6247d6bc378147c376
https://doi.org/10.1684/orthodfr.2022.78
https://doi.org/10.1684/orthodfr.2022.78
Autor:
Masrour MAKAREMI, Benoit MARCY, Ikram CHRAIBI KAADOUD, Alireza VAFAEI SADR, Ali Mohammad-Djafari, Salomé SADOUN, François DE BRONDEAU, Bernard N'KAOUA
Recent advances in the interpretability of convolutional neural networks (CNNs) have allowed applications in imaging as a novel method for visual feature extraction. We used this approach to investigate the impact of changing occlusal forces on crani
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c783b0e94f1d952b97ffd58766ce3bf
https://doi.org/10.21203/rs.3.rs-2544408/v1
https://doi.org/10.21203/rs.3.rs-2544408/v1
Publikováno v:
Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a83431ad93773974944863e343bb849c
https://doi.org/10.5220/0011363400003335
https://doi.org/10.5220/0011363400003335
Publikováno v:
Knowledge-Based Systems
Knowledge-Based Systems, Elsevier, 2021, 235, pp.18. ⟨10.1016/j.knosys.2021.107657⟩
Knowledge-Based Systems, 2021, 235, pp.18. ⟨10.1016/j.knosys.2021.107657⟩
Knowledge-Based Systems, Elsevier, 2021, pp.107657. ⟨10.1016/j.knosys.2021.107657⟩
Knowledge-Based Systems, Elsevier, 2021, 235, pp.18. ⟨10.1016/j.knosys.2021.107657⟩
Knowledge-Based Systems, 2021, 235, pp.18. ⟨10.1016/j.knosys.2021.107657⟩
Knowledge-Based Systems, Elsevier, 2021, pp.107657. ⟨10.1016/j.knosys.2021.107657⟩
We introduce a general method to extract knowledge from a recurrent neural network (Long Short Term Memory) that has learnt to detect if a given input sequence is valid or not, according to an unknown generative automaton. Based on the clustering of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23f6822922a25dfa438c020a35b53084
https://hal.inria.fr/hal-03437920/document
https://hal.inria.fr/hal-03437920/document
Publikováno v:
Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021
Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021, Aug 2021, Montréal, Canada. 2021
Twelfth International Workshop Modelling and Reasoning in Context
Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021, Aug 2021, Montréal (virtual), Canada. pp.28-40
HAL
Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021, Aug 2021, Montréal, Canada. 2021
Twelfth International Workshop Modelling and Reasoning in Context
Twelfth International Workshop Modelling and Reasoning in Context (MRC) @IJCAI 2021, Aug 2021, Montréal (virtual), Canada. pp.28-40
HAL
International audience; EXplainable Artificial Intelligence (XAI) has recently become a very active domain, mainly due to the extensive development of black-box models such as neural networks. Recent XAI objectives have been defined in the state-of-t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9000730ae9df76d0664cb897af33da52
https://hal.archives-ouvertes.fr/hal-03345286/file/2021-08-MRC-HCCS-IJCAI-POSTER.pdf
https://hal.archives-ouvertes.fr/hal-03345286/file/2021-08-MRC-HCCS-IJCAI-POSTER.pdf
Publikováno v:
Frontiers in Psychiatry
Frontiers in Psychiatry, Vol 12 (2021)
Frontiers in Psychiatry, Frontiers, 2021, 12, ⟨10.3389/fpsyt.2021.574440⟩
Frontiers in Psychiatry, Vol 12 (2021)
Frontiers in Psychiatry, Frontiers, 2021, 12, ⟨10.3389/fpsyt.2021.574440⟩
International audience; Artificial intelligence (AI) algorithms together with advances in data storage have recently made it possible to better characterize, predict, prevent, and treat a range of psychiatric illnesses. Amid the rapidly growing numbe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::539c9781121130540d802a4ca08a01ee
https://pubmed.ncbi.nlm.nih.gov/34630171
https://pubmed.ncbi.nlm.nih.gov/34630171