Deep residual correction network for partial domain adaptation

S Li, CH Liu, Q Lin, Q Wen, L Su… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …
被引用次数：157 相关文章

Deep Residual Correction Network for Partial Domain Adaptation

S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang… - arXiv e …, 2020 - ui.adsabs.harvard.edu
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …

Deep Residual Correction Network for Partial Domain Adaptation.

S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang… - IEEE Transactions on …, 2021 - europepmc.org
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …

Deep Residual Correction Network for Partial Domain Adaptation

S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang… - IEEE Transactions on …, 2021 - computer.org
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …

Deep Residual Correction Network for Partial Domain Adaptation

S Li, CH Liu, Q Lin, Q Wen, L Su… - … on pattern analysis …, 2021 - pubmed.ncbi.nlm.nih.gov
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …

Deep Residual Correction Network for Partial Domain Adaptation

S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang… - arXiv preprint arXiv …, 2020 - arxiv.org
Deep domain adaptation methods have achieved appealing performance by learning
transferable representations from a well-labeled source domain to a different but related …