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Domain Adaptive Classification
2013 IEEE International Conference on Computer Vision, 2013We propose an unsupervised domain adaptation method that exploits intrinsic compact structures of categories across different domains using binary attributes. Our method directly optimizes for classification in the target domain. The key insight is finding attributes that are discriminative across categories and predictable across domains. We achieve a
Fatemeh Mirrashed, Mohammad Rastegari
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2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Domain adaptation aims to transfer knowledge in the presence of the domain gap. Existing domain adaptation methods rely on rich prior knowledge about the relationship between the label sets of source and target domains, which greatly limits their application in the wild.
Kaichao You +4 more
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Domain adaptation aims to transfer knowledge in the presence of the domain gap. Existing domain adaptation methods rely on rich prior knowledge about the relationship between the label sets of source and target domains, which greatly limits their application in the wild.
Kaichao You +4 more
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2018
Learning with limited labeled data is always a challenge in AI problems, and one of promising ways is transferring well-established source domain knowledge to the target domain, i.e., domain adaptation. Recent researches on transfer learning exploit deep structures for discriminative feature representation to tackle cross-domain disparity. However, few
Zhengming Ding, Handong Zhao, Yun Fu
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Learning with limited labeled data is always a challenge in AI problems, and one of promising ways is transferring well-established source domain knowledge to the target domain, i.e., domain adaptation. Recent researches on transfer learning exploit deep structures for discriminative feature representation to tackle cross-domain disparity. However, few
Zhengming Ding, Handong Zhao, Yun Fu
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DAT: Domain Adaptive Transformer for Domain Adaptive Semantic Segmentation
2022 IEEE International Conference on Image Processing (ICIP), 2022Jinyoung Park +3 more
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Maximum Density Divergence for Domain Adaptation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Jingjing Li, Zhengming Ding, Lei Zhu
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Contrastive Adaptation Network for Single- and Multi-Source Domain Adaptation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Guoliang Kang, Lu Jiang, Yunchao Wei
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A Review of Domain Adaptation without Target Labels
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Wouter Marco Kouw, Marco Loog
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Human papillomavirus vaccination 2020 guideline update: American Cancer Society guideline adaptation
Ca-A Cancer Journal for Clinicians, 2020Robert A Smith
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Deep Residual Correction Network for Partial Domain Adaptation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Shuang Li, Chi Harold Liu, Qiuxia Lin
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Domain Adaptation for Medical Image Analysis: A Survey
IEEE Transactions on Biomedical Engineering, 2022Hao Guan, Mingxia Liu
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