{"id":"https://openalex.org/W4389352423","doi":"https://doi.org/10.1109/tgrs.2023.3339842","title":"Detail-Optimized Super-Resolution Reconstruction-Based Multistage Training Strategy for Remote Sensing Semantic Segmentation","display_name":"Detail-Optimized Super-Resolution Reconstruction-Based Multistage Training Strategy for Remote Sensing Semantic Segmentation","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4389352423","doi":"https://doi.org/10.1109/tgrs.2023.3339842"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3339842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3339842","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069851409","display_name":"Baikai Sui","orcid":"https://orcid.org/0000-0003-1244-5771"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baikai Sui","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080485606","display_name":"Yungang Cao","orcid":"https://orcid.org/0000-0003-0495-594X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yungang Cao","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003638009","display_name":"Haibo Cheng","orcid":"https://orcid.org/0000-0003-2275-0331"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibo Cheng","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007892503","display_name":"Shuang Zhang","orcid":"https://orcid.org/0000-0001-6963-3357"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Zhang","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114131902","display_name":"Jun Zhu","orcid":"https://orcid.org/0000-0003-1186-4392"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhu","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083261303","display_name":"Yakun Xie","orcid":"https://orcid.org/0000-0003-4213-2653"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yakun Xie","raw_affiliation_strings":["Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5069851409"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.7222,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73408568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7240966558456421},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6559743881225586},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6392393708229065},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.623075008392334},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5512109398841858},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5263572931289673},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5224977135658264},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46474024653434753},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42788177728652954},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.412426620721817},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.26419034600257874},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.07733926177024841}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7240966558456421},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6559743881225586},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6392393708229065},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.623075008392334},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5512109398841858},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5263572931289673},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5224977135658264},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46474024653434753},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42788177728652954},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.412426620721817},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.26419034600257874},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.07733926177024841},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3339842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3339842","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G4171306671","display_name":null,"funder_award_id":"2022YFC3005703","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4194738760","display_name":null,"funder_award_id":"2022NSFSC0409","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G8842547467","display_name":null,"funder_award_id":"41771451","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1911537302","https://openalex.org/W2114315281","https://openalex.org/W2242218935","https://openalex.org/W2331128040","https://openalex.org/W2414132572","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2603777577","https://openalex.org/W2607041014","https://openalex.org/W2792955223","https://openalex.org/W2891158090","https://openalex.org/W2900595774","https://openalex.org/W2901390297","https://openalex.org/W2927933146","https://openalex.org/W2962785568","https://openalex.org/W2963073614","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963677766","https://openalex.org/W2963814095","https://openalex.org/W2964170259","https://openalex.org/W2964309882","https://openalex.org/W2994610869","https://openalex.org/W2999691331","https://openalex.org/W3011024422","https://openalex.org/W3011248632","https://openalex.org/W3035022492","https://openalex.org/W3035028692","https://openalex.org/W3035570181","https://openalex.org/W3083065220","https://openalex.org/W3093647012","https://openalex.org/W3097155418","https://openalex.org/W3102061158","https://openalex.org/W3109301572","https://openalex.org/W3111683216","https://openalex.org/W3116492614","https://openalex.org/W3126818569","https://openalex.org/W3134260603","https://openalex.org/W3135471511","https://openalex.org/W3138368706","https://openalex.org/W3141797743","https://openalex.org/W3142105539","https://openalex.org/W3152981270","https://openalex.org/W3163026652","https://openalex.org/W3193508667","https://openalex.org/W3202420679","https://openalex.org/W3204971388","https://openalex.org/W3206098624","https://openalex.org/W3207918547","https://openalex.org/W3213555053","https://openalex.org/W4200174151","https://openalex.org/W4200519194","https://openalex.org/W4210522044","https://openalex.org/W4212902383","https://openalex.org/W4283031556","https://openalex.org/W4317033419","https://openalex.org/W4379746182","https://openalex.org/W6797399245"],"related_works":["https://openalex.org/W2362774332","https://openalex.org/W4249245269","https://openalex.org/W2025681766","https://openalex.org/W2765548132","https://openalex.org/W2159897444","https://openalex.org/W1522196789","https://openalex.org/W2542402767","https://openalex.org/W3023086044","https://openalex.org/W2142226356","https://openalex.org/W3210000161"],"abstract_inverted_index":{"Low":[0],"resolution":[1],"is":[2,39,109,141,215],"a":[3,30,65,97,180],"major":[4],"factor":[5],"that":[6,191],"negatively":[7],"impacts":[8],"the":[9,46,86,138,146,192,200,206,208,211,217],"accuracy":[10,57],"of":[11,48,58,148,199],"remote":[12],"sensing":[13],"(RS)":[14],"interpretation.":[15],"High-quality":[16],"super-resolution":[17,201],"reconstruction":[18,50],"(SRR)":[19],"can":[20,115],"help":[21],"alleviate":[22],"this":[23,26,124],"problem.":[24],"In":[25],"study,":[27],"we":[28,189],"present":[29],"multistage":[31],"semantic":[32,54],"segmentation":[33,55,103,135,186],"training":[34],"strategy":[35,125],"called":[36],"SRSSTS,":[37],"which":[38,73],"based":[40],"on":[41,155],"detail-optimized":[42],"SRR.":[43],"SRSSTS":[44,108,154],"addresses":[45],"challenges":[47],"poor":[49],"quality":[51],"and":[52,95,111,113,153,161,166,183],"low":[53],"(SS)":[56],"RS":[59,81,157],"images.":[60,82],"Our":[61],"approach":[62],"involves":[63],"constructing":[64],"generative":[66],"adversarial":[67],"network":[68,92,140,152],"(GAN)-based":[69],"perceptual-loss-dominated":[70],"SRR":[71,139,151],"network,":[72],"generates":[74],"texture-realistic,":[75],"high-quality":[76],"high-resolution":[77],"images":[78,88],"from":[79],"low-resolution":[80],"We":[83,144],"then":[84],"input":[85],"generated":[87],"into":[89],"an":[90,176],"SS":[91,120,177,218],"in":[93],"steps":[94],"propose":[96],"three-stage":[98],"joint":[99],"loss":[100],"to":[101,118,132,175],"generate":[102],"results":[104],"at":[105],"different":[106,169],"resolutions.":[107],"straightforward":[110],"efficient,":[112],"it":[114,214],"be":[116],"applied":[117],"any":[119],"backbone":[121],"networks.":[122],"Additionally,":[123],"does":[126],"not":[127],"increase":[128],"computational":[129],"resources":[130],"compared":[131,174],"other":[133,184],"SR-based":[134,185],"methods,":[136],"since":[137],"trained":[142],"separately.":[143],"evaluated":[145],"effectiveness":[147],"our":[149],"designed":[150],"five":[156],"datasets":[158],"(ISPRS":[159],"Potsdam":[160],"Vaihingen,":[162],"WHDLD,":[163],"LoveDA":[164],"Rural":[165],"Urban)":[167],"with":[168],"resolutions,":[170],"achieving":[171],"excellent":[172],"performance":[173],"model":[178],"for":[179,216],"single":[181],"task":[182],"methods.":[187],"Moreover,":[188],"observed":[190],"learned":[193],"perceptual":[194],"image":[195],"patch":[196],"similarity":[197],"(LPIPS)":[198],"(SR)":[202],"reconstructed":[203],"images,":[204],"i.e.,":[205],"stronger":[207],"perception":[209],"ability,":[210],"more":[212],"helpful":[213],"task.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}