S[sup.2]AC: Self-Supervised Attention Correlation Alignment Based on Mahalanobis Distance for Image...
S[sup.2]AC: Self-Supervised Attention Correlation Alignment Based on Mahalanobis Distance for Image Recognition
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Publisher
MDPI AG
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Language
English
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MDPI AG
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Contents
Susceptibility to domain changes for image classification hinders the application and development of deep neural networks. Domain adaptation (DA) makes use of domain-invariant characteristics to improve the performance of a model trained on labeled data from one domain (source domain) on an unlabeled domain (target) with a different data distributi...
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S[sup.2]AC: Self-Supervised Attention Correlation Alignment Based on Mahalanobis Distance for Image Recognition
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TN_cdi_gale_infotracacademiconefile_A772532098
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_gale_infotracacademiconefile_A772532098
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ISSN
2079-9292
E-ISSN
2079-9292
DOI
10.3390/electronics12214419
