{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:28:07Z","timestamp":1740101287924,"version":"3.37.3"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:00:00Z","timestamp":1671062400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62206168"],"award-info":[{"award-number":["62206168"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,15]]},"DOI":"10.1109\/icnsc55942.2022.10004109","type":"proceedings-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T21:35:28Z","timestamp":1673559328000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["SS8: Source Data-free Domain Adaptation via Deep Clustering with Weighted Self-labelling"],"prefix":"10.1109","author":[{"given":"Zihao","family":"Song","sequence":"first","affiliation":[{"name":"Institute of Machine Intelligence, University of Shanghai for Science and Technology,Shanghai,China"}]},{"given":"Lijuan","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Shanghai DianJi University,Shanghai,China"}]},{"given":"Han","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Machine Intelligence, University of Shanghai for Science and Technology,Shanghai,China"}]},{"given":"Guozhao","family":"Kou","sequence":"additional","affiliation":[{"name":"Institute of Machine Intelligence, University of Shanghai for Science and Technology,Shanghai,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2021.3110179"},{"key":"ref2","article-title":"Deep clustering for unsupervised learning of visual features","volume-title":"Proceedings of the European conference on computer vision (ECCV)","author":"Mathilde","year":"2018"},{"article-title":"Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation","volume-title":"International Conference on Machine Learning","author":"Jian","key":"ref3"},{"key":"ref4","article-title":"Casting a BAIT for offline and online source-free domain adaptation","author":"Shiqi","year":"2020","journal-title":"arXiv preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/584091.584093"},{"key":"ref6","article-title":"A kernel method for the two-sample problem","author":"Arthur","year":"2008","journal-title":"arXiv preprint"},{"article-title":"Learning transferable features with deep adaptation networks","volume-title":"International conference on machine learning","author":"Mingsheng","key":"ref7"},{"key":"ref8","article-title":"Generative adversarial nets","volume":"27","author":"Ian","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref9","article-title":"Adversarial discriminative domain adaptation","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Eric","year":"2017"},{"key":"ref10","article-title":"Transferable normalization: Towards improving transferability of deep neural networks","volume":"32","author":"Ximei","year":"2019","journal-title":"Advances in neural information processing systems"},{"article-title":"Adapting visual category models to new domains","volume-title":"European conference on computer vision","author":"Kate","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"article-title":"Unsupervised domain adaptation by backpropagation","volume-title":"International conference on machine learning","author":"Yaroslav","key":"ref14"},{"key":"ref15","article-title":"Conditional adversarial domain adaptation","volume":"31","author":"Mingsheng","year":"2018","journal-title":"Advances in neural information processing systems"},{"article-title":"Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation","volume-title":"International conference on machine learning","author":"Xinyang","key":"ref16"},{"key":"ref17","article-title":"Larger norm more transferable: An adaptive feature norm approach for unsupervised domain adaptation","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Ruijia","year":"2019"},{"key":"ref18","article-title":"Cluster alignment with a teacher for unsupervised domain adaptation","volume-title":"Proceedings of the IEEE\/CVF international conference on computer vision","author":"Zhijie","year":"2019"},{"article-title":"Dual mixup regularized learning for adversarial domain adaptation","volume-title":"European Conference on Computer Vision","author":"Yuan","key":"ref19"},{"article-title":"Implicit class-conditioned domain alignment for unsupervised domain adaptation","volume-title":"International Conference on Machine Learning","author":"Xiang","key":"ref20"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00400"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6137"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00966"},{"issue":"11","key":"ref24","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van der Maaten","year":"2008","journal-title":"Journal of machine learning research"},{"key":"ref25","article-title":"Deep residual learning for image recognition","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Kaiming","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636206"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00537"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/rs9080790"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014106"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.107"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00503"},{"article-title":"Instance adaptive self-training for unsupervised domain adaptation","volume-title":"European conference on computer vision","author":"Ke","key":"ref32"},{"article-title":"Two-phase pseudo label densification for self-training based domain adaptation","volume-title":"European conference on computer vision","author":"Inkyu","key":"ref33"},{"key":"ref34","article-title":"Theoretical analysis of self-training with deep networks on unlabeled data","author":"Colin","year":"2020","journal-title":"arXiv preprint"},{"key":"ref35","first-page":"17194","article-title":"A prototype-oriented framework for unsupervised domain adaptation","volume":"34","author":"Korawat","year":"2021","journal-title":"Advances in Neural Information Processing Systems"}],"event":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","start":{"date-parts":[[2022,12,15]]},"location":"Shanghai, China","end":{"date-parts":[[2022,12,18]]}},"container-title":["2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10004025\/10004026\/10004109.pdf?arnumber=10004109","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,9]],"date-time":"2024-02-09T02:48:09Z","timestamp":1707446889000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10004109\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,15]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/icnsc55942.2022.10004109","relation":{},"subject":[],"published":{"date-parts":[[2022,12,15]]}}}