{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T16:22:11Z","timestamp":1776529331431,"version":"3.51.2"},"reference-count":44,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,21]]},"DOI":"10.1109\/icpr56361.2022.9956437","type":"proceedings-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T19:34:13Z","timestamp":1669750453000},"page":"2900-2906","source":"Crossref","is-referenced-by-count":7,"title":["Discriminative Mutual Learning for Multi-target Domain Adaptation"],"prefix":"10.1109","author":[{"given":"Jie","family":"Wang","sequence":"first","affiliation":[{"name":"Fujitsu R&amp;D Center, Co., Ltd"}]},{"given":"Chaoliang","family":"Zhong","sequence":"additional","affiliation":[{"name":"Fujitsu R&amp;D Center, Co., Ltd"}]},{"given":"Cheng","family":"Feng","sequence":"additional","affiliation":[{"name":"Fujitsu R&amp;D Center, Co., Ltd"}]},{"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fujitsu R&amp;D Center, Co., Ltd"}]},{"given":"Jun","family":"Sun","sequence":"additional","affiliation":[{"name":"Fujitsu R&amp;D Center, Co., Ltd"}]},{"given":"Yasuto","family":"Yokota","sequence":"additional","affiliation":[{"name":"Fujitsu Ltd"}]}],"member":"263","reference":[{"key":"ref39","first-page":"212","article-title":"Improving neural networks by preventing co-adaptation of feature detectors","volume":"3","author":"hinton","year":"2012","journal-title":"Computer Science"},{"key":"ref38","article-title":"Automatic differentiation in pytorch","author":"paszke","year":"2017","journal-title":"NeurIPS workshop"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","article-title":"Unsupervised domain adaptation with residual transfer networks","author":"long","year":"2016","journal-title":"NeurIPS"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"ref30","article-title":"Cycle self-training for domain adaptation","author":"liu","year":"2021","journal-title":"NeurIPS"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00149"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.572"},{"key":"ref35","article-title":"Adapting visual category models to new domains","author":"saenko","year":"2010","journal-title":"ECCV"},{"key":"ref34","article-title":"Self-ensembling for visual domain adaptation","author":"french","year":"2018","journal-title":"ICLRE"},{"key":"ref10","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2016","journal-title":"JMLR"},{"key":"ref40","first-page":"315","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11767"},{"key":"ref12","article-title":"Learning semantic representations for unsupervised domain adaptation","author":"xie","year":"2018","journal-title":"ICML"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00072"},{"key":"ref14","article-title":"Unsupervised domain adaptation for semantic segmentation via class-balanced self-training","author":"zou","year":"2018","journal-title":"ECCV"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5757"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00235"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2963389"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01242"},{"key":"ref19","article-title":"Unsupervised multi-target domain adaptation through knowledge distillation","author":"le","year":"2021","journal-title":"WACV"},{"key":"ref28","article-title":"Co-teaching: Robust training of deep neural networks with extremely noisy labels","author":"han","year":"2018","journal-title":"NeurIPS"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995347"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref6","article-title":"Learning transferable features with deep adaptation networks","author":"long","year":"2015","journal-title":"ICML"},{"key":"ref29","article-title":"A discriminative feature learning approach for deep face recognition","author":"wen","year":"2016","journal-title":"ECCV"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2010.2091281"},{"key":"ref8","article-title":"Deep coral: Correlation alignment for deep domain adaptation","author":"sun","year":"2016","journal-title":"ECCV Workshops"},{"key":"ref7","article-title":"Deep transfer learning with joint adaptation networks","author":"long","year":"2017","journal-title":"ICML"},{"key":"ref2","article-title":"You only look once: Unified, real-time object detection","author":"redmon","year":"2015"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_36"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref20","article-title":"Domain agnostic learning with disentangled representations","author":"peng","year":"2019","journal-title":"ICML"},{"key":"ref22","first-page":"1645","article-title":"Conditional adversarial domain adaptation","author":"long","year":"2018","journal-title":"NeurIPS"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.316"},{"key":"ref42","article-title":"Semi-supervised learning by entropy minimization","author":"grandvalet","year":"2005","journal-title":"NeurIPS"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413284"},{"key":"ref41","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"ICML"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413022"},{"key":"ref44","first-page":"2579","article-title":"Visualizing data using t-sne","volume":"9","author":"laurens","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00531"},{"key":"ref43","article-title":"Larger norm more transferable: An adaptive feature norm approach for unsupervised domain adaptation","author":"xu","year":"2020","journal-title":"ICCV"},{"key":"ref25","article-title":"Heterogeneous graph attention network for unsupervised multiple-target domain adaptation","author":"yang","year":"2020","journal-title":"IEEE TPAMI"}],"event":{"name":"2022 26th International Conference on Pattern Recognition (ICPR)","location":"Montreal, QC, Canada","start":{"date-parts":[[2022,8,21]]},"end":{"date-parts":[[2022,8,25]]}},"container-title":["2022 26th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9956007\/9955631\/09956437.pdf?arnumber=9956437","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T20:05:03Z","timestamp":1671480303000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9956437\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,21]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/icpr56361.2022.9956437","relation":{},"subject":[],"published":{"date-parts":[[2022,8,21]]}}}