An improved low-complexity DenseUnet for high-accuracy iris segmentation network
An improved low-complexity DenseUnet for high-accuracy iris segmentation network
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Publisher
Amsterdam: IOS Press BV
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Language
English
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Publisher
Amsterdam: IOS Press BV
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Scope and Contents
Contents
Iris segmentation is one of the most important steps in iris recognition. The current iris segmentation network is based on convolutional neural network (CNN). Among these methods, there are still problems with the segmentation networks such as high complexity, insufficient accuracy, etc. To solve these problems, an improved low complexity DenseUne...
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Full title
An improved low-complexity DenseUnet for high-accuracy iris segmentation network
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TN_cdi_proquest_journals_2638058682
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2638058682
Other Identifiers
ISSN
1064-1246
E-ISSN
1875-8967
DOI
10.3233/JIFS-211396
