A Semi-Supervised Stacked Autoencoder Using the Pseudo Label for Classification Tasks

The efficiency and cognitive limitations of manual sample labeling result in a large number of unlabeled training samples in practical applications. Making full use of both labeled and unlabeled samples is the key to solving the semi-supervised problem. However, as a supervised algorithm, the stacke...

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Detalles Bibliográficos
Autores principales: Lai, Jie, Wang, Xiaodan, Xiang, Qian, Quan, Wen, Song, Yafei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528325/
https://www.ncbi.nlm.nih.gov/pubmed/37761573
http://dx.doi.org/10.3390/e25091274

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528325/
https://www.ncbi.nlm.nih.gov/pubmed/37761573
http://dx.doi.org/10.3390/e25091274

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