Transferable Feature Learning on Graphs Across Visual Domains
2021 IEEE International Conference on Multimedia and Expo (ICME)(2021)
摘要
Unsupervised domain adaptation adapts classifiers to an un-labeled target domain by exploiting a labeled source domain. To reduce discrepancy between source and target domains, adversarial learning methods are typically selected to seek domain-invariant representations by confusing the domain discriminator. However, classifiers may not be well adapted to such a domain-invariant representation spac...
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关键词
Learning systems,Visualization,Conferences,Benchmark testing,Data structures
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