{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T11:09:35Z","timestamp":1780052975102,"version":"3.54.0"},"reference-count":74,"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Satellite Information Application of Korea Aerospace Research Institute"},{"name":"Basic Science Research Program through the National Research Foundation of Korea"},{"name":"Ministry of Education","award":["2021R1A6A1A03044326"],"award-info":[{"award-number":["2021R1A6A1A03044326"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2024.3516519","type":"journal-article","created":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T19:18:58Z","timestamp":1734031138000},"page":"1727-1750","source":"Crossref","is-referenced-by-count":2,"title":["Fine-Tunned Segment Anything Model (SAM) for Reservoir Extractions Compared With Popular CNNs: An Experiment for Space-Borne Synthetic-Aperture Radar Images"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7657-624X","authenticated-orcid":false,"given":"Nguyen Hong","family":"Quang","sequence":"first","affiliation":[{"name":"Institute for Smart Infrastructure, Gangneung-Wonju National University, Gangneung-si, Gangwon-do, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7862-8306","authenticated-orcid":false,"given":"Hanna","family":"Lee","sequence":"additional","affiliation":[{"name":"Institute for Smart Infrastructure, Gangneung-Wonju National University, Gangneung-si, Gangwon-do, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2835-0526","authenticated-orcid":false,"given":"Eui-Myoung","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Drone and GIS Engineering, Namseoul University, Cheonan, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3280-5340","authenticated-orcid":false,"given":"Gihong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Gangneung-Wonju National University, Gangneung-si, Gangwon-do, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2018.2879492"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-archives-XLIII-B2-2020-1189-2020"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2024.114047"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2023.3335891"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898367"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ophoto.2021.100005"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2024.3351277"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2020.105823"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2018.01.017"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2021.3098678"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2017.2735443"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2017.2676343"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/w14071148"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3390\/rs14071752"},{"key":"ref17","volume-title":"Segment-anything-py: An\n                        unofficial Python package for meta AI\u2019s segment anything\n                        model","author":"Wu","year":"2023"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1017\/jog.2023.95"},{"key":"ref19","article-title":"Segment anything is not always perfect: An\n                        investigation of SAM on different real-world\n                    applications","author":"Ji","year":"2023","journal-title":"arXiv:2304.05750"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3332219"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-archives-XLVIII-4-W9-2024-383-2024"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2024.122964"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3356074"},{"key":"ref24","article-title":"A multispectral automated transfer technique (MATT)\n                        for machine-driven image labeling utilizing the segment anything model\n                        (SAM)","author":"Gallagher","year":"2024","journal-title":"arXiv:2402.11413"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/hydrology11020017"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3385425"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3392778"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-023-01951-4"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2024.3357777"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2024.3368168"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2023.103540"},{"key":"ref32","first-page":"1","article-title":"Segment any stream: Scalable water extent detection\n                        with the segment anything model","volume-title":"Proc.\n                        NeurIPS","author":"Zheng"},{"key":"ref33","article-title":"SAM fails to segment\n                        anything?\u2014SAM-adapter: Adapting SAM in underperformed scenes:\n                        Camouflage, shadow, and more","author":"Chen","year":"2023","journal-title":"arXiv:2304.09148"},{"key":"ref34","article-title":"Segment anything in high\n                    quality","author":"Ke","year":"2023","journal-title":"arXiv:2306.01567"},{"key":"ref35","article-title":"Adapting segment anything model for change detection\n                        in HR remote sensing images","author":"Ding","year":"2023","journal-title":"arXiv:2309.01429"},{"key":"ref36","article-title":"SAM-assisted remote sensing imagery semantic\n                        segmentation with object and boundary constraints","author":"Ma","year":"2023","journal-title":"arXiv:2312.02464"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.21105\/joss.03414"},{"key":"ref38","volume-title":"Rasterio: Geospatial Raster I\/O for Python\n                        Programmers","author":"Gillies","year":"2013"},{"key":"ref39","volume-title":"geopandas\/geopandas: v0.5.0","author":"Jordahl","year":"2019"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00817"},{"issue":"5","key":"ref41","first-page":"656","article-title":"Generality and specificity of landforms of the Korean\n                        peninsula, and its sustainability","volume":"49","author":"Park","year":"2014","journal-title":"J. Korean\n                        geographical Soc."},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2017.07.061"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s10201-001-8040-6"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.3390\/make5040083"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-0213-0_13"},{"key":"ref46","first-page":"8748","article-title":"Learning transferable visual models from natural\n                        language supervision","volume-title":"Proc. Int. Conf.\n                        Mach. Learn.","author":"Radford"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3094201"},{"key":"ref48","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"arXiv:1706.03762"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3403902"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/INOCON60754.2024.10511858"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3390\/app131810145"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TELFOR.2018.8611986"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2021.112467"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2018.8621865"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2019.00135"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3138920"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3081818"},{"key":"ref59","volume-title":"YOLOv8","year":"2024"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.3741\/JKWRA.2008.41.2.185"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/978-90-481-3751-0_1"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2024.3350120"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.13028"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122212"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121209"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2011.02.006"},{"key":"ref68","article-title":"PP-YOLO: An effective and efficient implementation of\n                        object detector","author":"Long","year":"2020","journal-title":"arXiv:2007.12099"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1038\/srep36405"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrh.2023.101619"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00444-8"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1007\/s12145-024-01428-x"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-014-0007-7"},{"key":"ref74","article-title":"Spurious correlations in machine learning: A\n                        survey","author":"Ye","year":"2024","journal-title":"arXiv:2402.12715"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10795130.pdf?arnumber=10795130","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,18]],"date-time":"2025-03-18T04:44:44Z","timestamp":1742273084000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10795130\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":74,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3516519","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}