A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification

This paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-en...

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Detalles Bibliográficos
Autores principales: Karim, Ahmad M., Kaya, Hilal, Güzel, Mehmet Serdar, Tolun, Mehmet R., Çelebi, Fatih V., Mishra, Alok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664945/
https://www.ncbi.nlm.nih.gov/pubmed/33182270
http://dx.doi.org/10.3390/s20216378

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664945/
https://www.ncbi.nlm.nih.gov/pubmed/33182270
http://dx.doi.org/10.3390/s20216378

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