{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:12:39Z","timestamp":1774627959627,"version":"3.50.1"},"reference-count":70,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["OIA-1946391 (RII Track-1)"],"award-info":[{"award-number":["OIA-1946391 (RII Track-1)"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2223793(EFRI BRAID)"],"award-info":[{"award-number":["2223793(EFRI BRAID)"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2119691 (AI SUSTEIN)"],"award-info":[{"award-number":["2119691 (AI SUSTEIN)"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2345176"],"award-info":[{"award-number":["2345176"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Smart Grid"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/tsg.2025.3531764","type":"journal-article","created":{"date-parts":[[2025,2,5]],"date-time":"2025-02-05T18:55:22Z","timestamp":1738781722000},"page":"2611-2623","source":"Crossref","is-referenced-by-count":4,"title":["S3Former: A Deep Learning Approach to High Resolution Solar PV Profiling"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1468-0476","authenticated-orcid":false,"given":"Minh","family":"Tran","sequence":"first","affiliation":[{"name":"EECS Department, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian De","family":"Luis","sequence":"additional","affiliation":[{"name":"EECS Department, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1050-7086","authenticated-orcid":false,"given":"Haitao","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4119-9522","authenticated-orcid":false,"given":"Ying","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, North Dakota State University, Fargo, ND, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6480-0099","authenticated-orcid":false,"given":"Roy","family":"McCann","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6447-5345","authenticated-orcid":false,"given":"Alan","family":"Mantooth","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jackson","family":"Cothren","sequence":"additional","affiliation":[{"name":"Geosciences Department, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2571-0511","authenticated-orcid":false,"given":"Ngan","family":"Le","sequence":"additional","affiliation":[{"name":"EECS Department, University of Arkansas, Fayetteville, AR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joule.2019.07.028"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2023.113571"},{"key":"ref3","volume-title":"Record U.S. Small-Scale Solar Capacity was Added in 2022","year":"2023"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2022.03.041"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2502140"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.joule.2018.11.021"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.gloenvcha.2012.11.006"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-019-07942-1"},{"key":"ref9","first-page":"4243","article-title":"Assessing land suitability for managing urban growth: An application of GIS and RS","volume-title":"Proc. IEEE Int. Geosci. Remote Sens. Symp.","author":"Pooja"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.4236\/jgis.2013.56054"},{"key":"ref11","article-title":"LoveDA: A remote sensing land-cover dataset for domain adaptive semantic segmentation","author":"Wang","year":"2022","journal-title":"arXiv:2110.08733"},{"key":"ref12","first-page":"1","article-title":"Towards unsupervised assessment with open-source data of the accuracy of deep learning-based distributed PV mapping","volume-title":"Proc. Workshop Mach. Learn. Earth Obs. (MACLEAN)","author":"Kasmi"},{"key":"ref13","article-title":"HyperionSolarNet: Solar panel detection from aerial images","author":"Parhar","year":"2022","journal-title":"arXiv:2201.02107"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01054"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01202"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/rs15204987"},{"key":"ref19","article-title":"SolarFormer: Multi-scale transformer for solar PV profiling","author":"de Luis","year":"2023","journal-title":"arXiv:2310.20057"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3386402"},{"key":"ref22","article-title":"DINOv2: Learning robust visual features without supervision","author":"Oquab","year":"2024","journal-title":"arXiv:2304.07193"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3415112"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.106"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-01951-4"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2016.08.191"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2017.8127092"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106283"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/PVSC45281.2020.9300636"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.118469"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2010.11929"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.15439\/2020F20"},{"key":"ref34","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Touvron"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP46576.2022.9897766"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i3.25412"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01727"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/IEEECONF56349.2022.10052051"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-022-01702-9"},{"key":"ref40","article-title":"HENASY: Learning to assemble scene-entities for egocentric video-language model","author":"Vo","year":"2024","journal-title":"arXiv:2406.00307"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01422"},{"key":"ref42","first-page":"1","article-title":"AISFormer: Amodal instance segmentation with transformer","volume-title":"Proc. BMVC","author":"Tran"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00297"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00202"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01118"},{"key":"ref46","article-title":"A simple framework for contrastive learning of visual representations","author":"Chen","year":"2020","journal-title":"arXiv:2002.05709"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2496141"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref49","article-title":"Unsupervised feature learning via non-parametric instance-level discrimination","author":"Wu","year":"2018","journal-title":"arXiv:1805.01978"},{"key":"ref50","first-page":"1","article-title":"Noise-contrastive estimation: A new estimation principle for unnormalized statistical models","volume-title":"Proc. Int. Conf. Artif. Intell. Stat.","author":"Gutmann"},{"key":"ref51","article-title":"Self-labelling via simultaneous clustering and representation learning","author":"Asano","year":"2020","journal-title":"arXiv:1911.05371"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00305"},{"key":"ref53","article-title":"Bootstrap your own latent: A new approach to self-supervised learning","author":"Grill","year":"2020","journal-title":"arXiv:2006.07733"},{"key":"ref54","article-title":"Exploring simple Siamese representation learning","author":"Chen","year":"2020","journal-title":"arXiv:2011.10566"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00696"},{"key":"ref56","article-title":"Barlow twins: Self-supervised learning via redundancy reduction","author":"Zbontar","year":"2021","journal-title":"arXiv:2103.03230"},{"key":"ref57","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","author":"Tarvainen","year":"2018","journal-title":"arXiv:1703.01780"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref59","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015","journal-title":"arXiv:1409.1556"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1038\/355161a0"},{"key":"ref63","first-page":"1","article-title":"Distilling the knowledge in a neural network","volume-title":"Proc. NIPS Deep Learn. Represent. Learn. Workshop","author":"Hinton"},{"key":"ref64","article-title":"Deformable DETR: Deformable transformers for end-to-end object detection","author":"Zhu","year":"2021","journal-title":"arXiv:2010.04159"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01228-1_26"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"ref69","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2017","journal-title":"arXiv:1412.6980"},{"key":"ref70","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"Chen","year":"2017","journal-title":"arXiv:1706.05587"}],"container-title":["IEEE Transactions on Smart Grid"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/5165411\/10974423\/10874220-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5165411\/10974423\/10874220.pdf?arnumber=10874220","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T17:57:17Z","timestamp":1745431037000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10874220\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":70,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tsg.2025.3531764","relation":{},"ISSN":["1949-3053","1949-3061"],"issn-type":[{"value":"1949-3053","type":"print"},{"value":"1949-3061","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}