A Few-Shot Object Detection Method for Endangered Species
A Few-Shot Object Detection Method for Endangered Species
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Full title
Author / Creator
Publisher
Basel: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Basel: MDPI AG
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Scope and Contents
Contents
Endangered species detection plays an important role in biodiversity conservation and is significant in maintaining ecological balance. Existing deep learning-based object detection methods are overly dependent on a large number of supervised samples, and building such endangered species datasets is usually costly. Aiming at the problems faced by e...
Alternative Titles
Full title
A Few-Shot Object Detection Method for Endangered Species
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_bde104e8a6ce40958f34358dce2d0c91
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_bde104e8a6ce40958f34358dce2d0c91
Other Identifiers
ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app14114443
