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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...
Autores principales: | Karim, Ahmad M., Kaya, Hilal, Güzel, Mehmet Serdar, Tolun, Mehmet R., Çelebi, Fatih V., Mishra, Alok |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
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 |
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