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| Learning Domain Invariant Representation via Self-Rugularization |
| Jaeguk Hyun, ChanYong Lee, Hoseong Kim, Hyunjung Yoo, Eunjin Koh |
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J. KIMS Technol. 2021;24(4):382-391. Published online August 5, 2021 DOI: https://doi.org/10.9766/KIMST.2021.24.4.382 |
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Learning Domain Invariant Representation via Self-Rugularization Journal of the Korea Institute of Military Science and Technology. 2021;24(4):382-391  Meta-learning the invariant representation for domain generalization Machine Learning. 2022; Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle Pattern Recognition. 2015;48(10):2964-2982 Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020; Conditional entropy minimization principle for learning domain invariant representation features 2022 26th International Conference on Pattern Recognition (ICPR). 2022; Unsupervised domain adaptation via representation learning and adaptive classifier learning Neurocomputing. 2015;165:300-311 Learning intra-domain style-invariant representation for unsupervised domain adaptation of semantic segmentation Pattern Recognition. 2022;132:108911 Domain-invariant representation learning using an unsupervised domain adversarial adaptation deep neural network Neurocomputing. 2019;355:209-220 Self-Supervised Representation Learning From Multi-Domain Data 2019 IEEE/CVF International Conference on Computer Vision (ICCV). 2019; Cross-Domain Face Presentation Attack Detection via Multi-Domain Disentangled Representation Learning 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2020; |
