Shift-and-Balance Attention
Shift-and-Balance Attention
About this item
Full title
Shift-and-Balance Attention
Author / Creator
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
arXiv.org, 2021-03
Language
English
Formats
Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
Subjects
More information
Scope and Contents
Contents
Attention is an effective mechanism to improve the deep model capability. Squeeze-and-Excite (SE) introduces a light-weight attention branch to enhance the network's representational power. The attention branch is gated using the Sigmoid function and multiplied by the feature map's trunk branch. It is too sensitive to coordinate and balance the tru...
Alternative Titles
Full title
Shift-and-Balance Attention
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2505021078
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2505021078
Other Identifiers
E-ISSN
2331-8422
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