{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T14:43:14Z","timestamp":1770734594291,"version":"3.49.0"},"reference-count":74,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012236","name":"Beijing Institute of Technology Research Fund Program for Young Scholars","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012236","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1109\/tmc.2025.3614353","type":"journal-article","created":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T17:57:33Z","timestamp":1758823053000},"page":"3279-3296","source":"Crossref","is-referenced-by-count":1,"title":["mmWave Radar-Based Unsupervised Gesture Recognition via Image-Aligned Heterogeneous Domain Transfer"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8523-5391","authenticated-orcid":false,"given":"Qihua","family":"Feng","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-5718-0343","authenticated-orcid":false,"given":"Kunpeng","family":"Cheng","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9290-8272","authenticated-orcid":false,"given":"Chunhui","family":"Duan","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3432235"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3477003"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.781"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1049\/iet-cvi.2017.0052"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3284496"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2023.3298300"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3381010"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3105387"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2025.3592965"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3436729"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3448110"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3207570"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430733"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3517231"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3028503"},{"key":"ref16","first-page":"97","article-title":"Learning transferable features with deep adaptation networks","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"37","author":"Long","year":"2015"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58347-1_10"},{"key":"ref18","first-page":"1647","article-title":"Conditional adversarial domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Long","year":"2018"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00532"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref21","article-title":"A-z handwritten alphabets"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ijcnn.2017.7966217"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5745"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00072"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6091"},{"key":"ref26","article-title":"Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re-identification","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Ge","year":"2020"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445138"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3580872"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3325399"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3427406"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488789"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/DCOSS.2019.00028"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM48880.2022.9796905"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3560905.3568506"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3372224.3419982"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref39","first-page":"5099","article-title":"PointNet : Deep hierarchical feature learning on point sets in a metric space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Qi","year":"2017"},{"key":"ref40","article-title":"Texas instruments"},{"key":"ref41","article-title":"A review of CFAR detection techniques in radar systems","volume":"29","author":"Farina","year":"1986","journal-title":"Microw. J."},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19836-6_15"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2011.5980567"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.5815\/ijisa.2014.05.09"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1021\/ac60214a047"},{"issue":"11","key":"ref46","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/11536406_16"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3400066"},{"key":"ref51","first-page":"896","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop Challenges Representation Learn.","volume":"3","author":"Lee","year":"2013"},{"key":"ref52","first-page":"1","article-title":"Adversarial self-training improves robustness and generalization for gradual domain adaptation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Shi","year":"2023"},{"key":"ref53","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Goodfellow","year":"2015"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.5555\/3104322.3104425"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-0255(96)00200-9"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3455008"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-demos.6"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2025.103153"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3370668"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2025.3576692"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3171312"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00392"},{"key":"ref65","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"70","author":"Long","year":"2017"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01499"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3185233"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3066507"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/2789168.2790113"},{"key":"ref70","article-title":"Multi-source domain adaptation in the deep learning era: A systematic survey","volume":"abs\/2002.12169","author":"Zhao","year":"2020","journal-title":"CoRR"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3380981"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3170157"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2909249"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM52122.2024.10621091"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7755\/11372515\/11180134.pdf?arnumber=11180134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:10:20Z","timestamp":1770671420000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11180134\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":74,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2025.3614353","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3]]}}}