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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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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 |