{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T02:48:10Z","timestamp":1768013290062,"version":"3.49.0"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3147063","type":"journal-article","created":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T22:32:40Z","timestamp":1643322760000},"page":"12322-12333","source":"Crossref","is-referenced-by-count":15,"title":["Channel Attention GAN Trained With Enhanced Dataset for Single-Image Shadow Removal"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7369-1530","authenticated-orcid":false,"given":"Ryo","family":"Abiko","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3461-1507","authenticated-orcid":false,"given":"Masaaki","family":"Ikehara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2009.2026682"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.11.020"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2803179"},{"key":"ref4","article-title":"Image segmentation in video sequences: A probabilistic approach","author":"Friedman","year":"2013","journal-title":"arXiv:1302.1539"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.43"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00192"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.23919\/Eusipco47968.2020.9287528"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.157"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2012.2208976"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.214"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.5244\/C.28.36"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.248"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2919616"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00867"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00256"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6695"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01043"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_26"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00778"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2008.01155.x"},{"key":"ref21","article-title":"Mish: A self regularized non-monotonic activation function","author":"Misra","year":"2019","journal-title":"arXiv:1908.08681"},{"key":"ref22","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ioffe"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_48"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2947266"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.2307\/j.ctvcm4g18.8"},{"key":"ref30","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535302"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.579"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09694637.pdf?arnumber=9694637","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T22:13:28Z","timestamp":1705184008000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9694637\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3147063","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}