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Inverse Feature Learning: Feature Learning Based on Representation Learning of Error

This paper proposes inverse feature learning (IFL) as a novel supervised feature learning technique that learns a set of high-level features for classification based on an error representation approach. The key contribution of this method is to learn the representation of error as high-level feature...

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Detalles Bibliográficos
Autores principales: GHAZANFARI, BEHZAD, AFGHAH, FATEMEH, HAJIAGHAYI, MOHAMMADTAGHI
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356800/
https://www.ncbi.nlm.nih.gov/pubmed/34386308
http://dx.doi.org/10.1109/access.2020.3009902

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