Normalized group activations based feature extraction technique using heterogeneous data for Alzheim...
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimer's disease classification
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Publisher
United States: PeerJ. Ltd
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Language
English
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Publisher
United States: PeerJ. Ltd
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Contents
Several deep learning networks are developed to identify the complex atrophic patterns of Alzheimer's disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one. Even though these functions are analyzed individually, group activations and their interpretations are still not explored...
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Full title
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimer's disease classification
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TN_cdi_doaj_primary_oai_doaj_org_article_65579e6e8cd0481eb18f1ddf8088ba08
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_65579e6e8cd0481eb18f1ddf8088ba08
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ISSN
2376-5992
E-ISSN
2376-5992
DOI
10.7717/peerj-cs.2502
