{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T06:31:42Z","timestamp":1762497102848,"version":"build-2065373602"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":["62376283","62022091","62201588","62401585","62531026"],"award-info":[{"award-number":["62376283","62022091","62201588","62401585","62531026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tgrs.2025.3621519","type":"journal-article","created":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T17:40:04Z","timestamp":1760463604000},"page":"1-16","source":"Crossref","is-referenced-by-count":0,"title":["Observations Temporal Permutation-Based Self-Supervised Reinforcement Learning for UAV Active Object Detection"],"prefix":"10.1109","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1379-7456","authenticated-orcid":false,"given":"Xinhua","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2522-656X","authenticated-orcid":false,"given":"Tianpeng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2011-2873","authenticated-orcid":false,"given":"Li","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1233-1494","authenticated-orcid":false,"given":"Zhen","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0682-8365","authenticated-orcid":false,"given":"Yongxiang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2025.3533019"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3362877"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2024.3352660"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3395483"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging6080078"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2020.104046"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2021.107261"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3150988"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3193019"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2022.3191745"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989164"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2018.8489296"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2890849"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2021.3090707"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2840991"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-024-00863-1"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2025.3566604"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1177\/0278364911410755"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.103"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3157028"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00319"},{"key":"ref22","article-title":"Unsupervised representation learning in deep reinforcement learning: A review","author":"Botteghi","year":"2022","journal-title":"arXiv:2208.14226"},{"key":"ref23","first-page":"2170","article-title":"DeepMDP: Learning continuous latent space models for representation learning","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Gelada"},{"key":"ref24","article-title":"Learning invariant representations for reinforcement learning without reconstruction","author":"Zhang","year":"2020","journal-title":"arXiv:2006.10742"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i6.28369"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctt4cgngj.10"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561103"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1613\/jair.3912"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpa.2020.100022"},{"key":"ref30","first-page":"6074","article-title":"DRIBO: Robust deep reinforcement learning via multi-view information bottleneck","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Fan"},{"key":"ref31","article-title":"Feature-attending recurrent modules for generalization in reinforcement learning","author":"Carvalho","year":"2021","journal-title":"arXiv:2112.08369"},{"key":"ref32","first-page":"3480","article-title":"Learning task informed abstractions","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Fu"},{"key":"ref33","first-page":"9870","article-title":"Decoupling representation learning from reinforcement learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Stooke"},{"key":"ref34","first-page":"13022","article-title":"Pre-trained image encoder for generalizable visual reinforcement learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yuan"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01441"},{"key":"ref36","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"139","author":"Radford"},{"key":"ref37","article-title":"Dinov2: Learning robust visual features without supervision","author":"Oquab","year":"2023","journal-title":"arXiv:2304.07193"},{"key":"ref38","first-page":"25502","article-title":"Why generalization in RL is difficult: Epistemic POMDPs and implicit partial observability","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ghosh"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref41","first-page":"1154","article-title":"Offline reinforcement learning from images with latent space models","volume-title":"Proc. 3rd Conf. Learn. Dyn. Control","author":"Rafailov"},{"key":"ref42","first-page":"8229","article-title":"Learning Markov state abstractions for deep reinforcement learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Allen"},{"key":"ref43","article-title":"Representation learning with contrastive predictive coding","author":"Oord","year":"2018","journal-title":"arXiv:1807.03748"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11798"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/36\/10807682\/11203001.pdf?arnumber=11203001","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T06:25:53Z","timestamp":1762496753000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11203001\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2025.3621519","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"type":"print","value":"0196-2892"},{"type":"electronic","value":"1558-0644"}],"subject":[],"published":{"date-parts":[[2025]]}}}