{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T16:02:28Z","timestamp":1780588948352,"version":"3.54.1"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Nature Science Foundation of China","award":["61876049"],"award-info":[{"award-number":["61876049"]}]},{"name":"Nature Science Foundation of China","award":["61762066"],"award-info":[{"award-number":["61762066"]}]},{"name":"Guangxi Key Laboratory of Image"},{"name":"Graphic Intelligent Processing","award":["GIIP2006"],"award-info":[{"award-number":["GIIP2006"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["2019YCXS043"],"award-info":[{"award-number":["2019YCXS043"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["YCBZ2018052"],"award-info":[{"award-number":["YCBZ2018052"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/lsp.2021.3077801","type":"journal-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T19:31:08Z","timestamp":1620329468000},"page":"982-986","source":"Crossref","is-referenced-by-count":103,"title":["Infrared Image Super-Resolution via Transfer Learning and PSRGAN"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3114-9206","authenticated-orcid":false,"given":"Yongsong","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zetao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9488-8236","authenticated-orcid":false,"given":"Rushi","family":"Lan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoqin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kui","family":"Pi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","article-title":"Adam:A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2017.05.007"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1142\/S0219691318500182"},{"key":"ref30","article-title":"Adapting pedestrian detection from synthetic to far infrared images","author":"socarras","year":"0","journal-title":"Proc ICCV - Workshop Vis Domain Adapt Dataset Bias"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"ref11","first-page":"5407","article-title":"Closed-loop matters:Dual regression networks for single image super-resolution","author":"guo","year":"0","journal-title":"Proc IEEE Conf CVPR"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00051"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00779"},{"key":"ref14","article-title":"Wasserstein GAN","author":"arjovsky","year":"2017"},{"key":"ref15","article-title":"A review on generative adversarial networks:Algorithms, theory, and applications","author":"gui","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2864777"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/SIPROCESS.2019.8868566"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-019-01511-7"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00243"},{"key":"ref4","first-page":"63","article-title":"ESRGAN:Enhanced super-resolution generative adversarial networks","author":"wang","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3001940"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s11938-020-00287-x"},{"key":"ref6","first-page":"3565","article-title":"Aim 2019 challenge on constrained super-resolution:Methods and results","author":"zhang","year":"0","journal-title":"Proc IEEE\/CVF Int Conf Comput Vis Workshop (ICCVW)"},{"key":"ref29","first-page":"114","article-title":"Ntire 2017 challenge on single image super-resolution:Methods and results","author":"timofte","year":"0","journal-title":"Proc IEEE Conf CVPR"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00177"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00344"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2017.2655112"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20870-7_2"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-009-5152-4"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.01.025"},{"key":"ref24","first-page":"1251","article-title":"Xception:Deep learning with depthwise separable convolutions","author":"chollet","year":"0","journal-title":"Proc IEEE Conf CVPR"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/35016072"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00726"},{"key":"ref25","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/97\/9325893\/09424970.pdf?arnumber=9424970","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:32Z","timestamp":1652194232000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9424970\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/lsp.2021.3077801","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}