On the Behavior of Convolutional Nets for Feature Extraction
On the Behavior of Convolutional Nets for Feature Extraction
About this item
Full title
Author / Creator
Publisher
San Francisco: AI Access Foundation
Journal title
Language
English
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Publication information
Publisher
San Francisco: AI Access Foundation
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Scope and Contents
Contents
Deep neural networks are representation learning techniques. During training, a deep net is capable of generating a descriptive language of unprecedented size and detail in machine learning. Extracting the descriptive language coded within a trained CNN model (in the case of image data), and reusing it for other purposes is a field of interest, as...
Alternative Titles
Full title
On the Behavior of Convolutional Nets for Feature Extraction
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_csuc_recercat_oai_recercat_cat_2072_309521
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_csuc_recercat_oai_recercat_cat_2072_309521
Other Identifiers
ISSN
1076-9757
E-ISSN
1076-9757,1943-5037
DOI
10.1613/jair.5756
