Cargando…
Non-smooth Bayesian learning for artificial neural networks
Artificial neural networks (ANNs) are being widely used in supervised machine learning to analyze signals or images for many applications. Using an annotated learning database, one of the main challenges is to optimize the network weights. A lot of work on solving optimization problems or improving...
Autores principales: | Fakhfakh, Mohamed, Chaari, Lotfi, Bouaziz, Bassem, Gargouri, Faiez |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244188/ https://www.ncbi.nlm.nih.gov/pubmed/35789599 http://dx.doi.org/10.1007/s12652-022-04073-8 |
Ejemplares similares
-
A Convolutional Neural Network for Lentigo Diagnosis
por: Zorgui, Sana, et al.
Publicado: (2020) -
Convolutional Neural Network for Drowsiness Detection Using EEG Signals
por: Chaabene, Siwar, et al.
Publicado: (2021) -
EEG-Based Hypo-vigilance Detection Using Convolutional Neural Network
por: Boudaya, Amal, et al.
Publicado: (2020) -
Bayesian learning for neural networks
por: Neal, Radford M
Publicado: (1996) -
Condition Monitoring of Machinery in Non-Stationary Operations : Proceedings of the Second International Conference "Condition Monitoring of Machinery in Non-Stationnary Operations"
por: Fakhfakh, Tahar, et al.
Publicado: (2012)