{"id":"https://openalex.org/W4396782842","doi":"https://doi.org/10.1109/tgrs.2024.3399260","title":"EasySeg: An Error-Aware Domain Adaptation Framework for Remote Sensing Imagery Semantic Segmentation via Interactive Learning and Active Learning","display_name":"EasySeg: An Error-Aware Domain Adaptation Framework for Remote Sensing Imagery Semantic Segmentation via Interactive Learning and Active Learning","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396782842","doi":"https://doi.org/10.1109/tgrs.2024.3399260"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3399260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3399260","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/A5021434142","display_name":"Liangzhe Yang","orcid":"https://orcid.org/0000-0001-7894-3170"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangzhe Yang","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"raw_orcid":"https://orcid.org/0000-0001-7894-3170","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353589","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0002-7880-3394"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Chen","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China","Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, China"],"raw_orcid":"https://orcid.org/0000-0002-7880-3394","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, China","institution_ids":["https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046115734","display_name":"Anran Yang","orcid":"https://orcid.org/0000-0001-6106-759X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anran Yang","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100361659","display_name":"Jun Li","orcid":"https://orcid.org/0000-0001-7055-7873"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8328,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86987151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9868999719619751,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9815999865531921,"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":0.8599804639816284},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6846238374710083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6491681933403015},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.48054081201553345},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46556782722473145},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.45704227685928345},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44595858454704285},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.44580331444740295},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4140129089355469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35096317529678345}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8599804639816284},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6846238374710083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6491681933403015},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.48054081201553345},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46556782722473145},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.45704227685928345},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44595858454704285},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.44580331444740295},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4140129089355469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35096317529678345},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3399260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3399260","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W2162651021","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2771766796","https://openalex.org/W2935033494","https://openalex.org/W2963073217","https://openalex.org/W2963107255","https://openalex.org/W2964309882","https://openalex.org/W2969893028","https://openalex.org/W2981952612","https://openalex.org/W2992308087","https://openalex.org/W3034417116","https://openalex.org/W3034590424","https://openalex.org/W3035294798","https://openalex.org/W3107502112","https://openalex.org/W3108566666","https://openalex.org/W3109470472","https://openalex.org/W3132926949","https://openalex.org/W3138516171","https://openalex.org/W3182214289","https://openalex.org/W3200974967","https://openalex.org/W3201926993","https://openalex.org/W3202165894","https://openalex.org/W3203473630","https://openalex.org/W3203978358","https://openalex.org/W3204469733","https://openalex.org/W3210646956","https://openalex.org/W4205379033","https://openalex.org/W4206603952","https://openalex.org/W4221161877","https://openalex.org/W4229723800","https://openalex.org/W4282553729","https://openalex.org/W4285512371","https://openalex.org/W4293215018","https://openalex.org/W4312310512","https://openalex.org/W4312336332","https://openalex.org/W4312507102","https://openalex.org/W4312599869","https://openalex.org/W4313460427","https://openalex.org/W4318814448","https://openalex.org/W4318903367","https://openalex.org/W4320005441","https://openalex.org/W4327695706","https://openalex.org/W4383890300","https://openalex.org/W4386075981","https://openalex.org/W4386223445","https://openalex.org/W4388757367","https://openalex.org/W6746282794","https://openalex.org/W6767268582","https://openalex.org/W6785293073","https://openalex.org/W6802946413","https://openalex.org/W6849689160"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2997567050","https://openalex.org/W2611989081","https://openalex.org/W1483272040","https://openalex.org/W4283377908","https://openalex.org/W1533421371","https://openalex.org/W2003050223","https://openalex.org/W4230611425","https://openalex.org/W4394775207","https://openalex.org/W3112772842"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,153,161],"of":[2,206,218,234],"remote":[3,81,105],"sensing":[4,82,106],"images":[5,75,83],"has":[6,43],"attracted":[7],"much":[8],"attention":[9],"for":[10,104],"its":[11],"wide":[12],"applications.":[13],"While":[14],"deep":[15],"learning":[16,114,133],"models":[17],"have":[18],"shown":[19],"impressive":[20],"performance":[21,182],"in":[22,204],"this":[23,50,94],"task,":[24],"challenges":[25,77],"arise":[26],"when":[27,78],"applying":[28],"them":[29],"to":[30,38,48,80,85,141,178],"data":[31],"from":[32],"other":[33],"domains":[34],"without":[35],"fine-tuning,":[36],"due":[37,84],"domain":[39,58,69,87,101,180,201],"gaps.":[40],"Domain":[41],"adaptation":[42,70,102,181,202],"emerged":[44],"as":[45],"a":[46,98,121],"solution":[47],"bridge":[49],"gap.":[51],"Existing":[52],"works":[53],"mainly":[54],"focus":[55],"on":[56,73,166,190],"unsupervised":[57],"adaptation,":[59],"which":[60,156],"lags":[61],"far":[62],"behind":[63],"fully":[64,228],"supervised":[65,229],"models.":[66,230],"However,":[67],"active":[68,116,132,200],"methods":[71,203],"focused":[72],"natural":[74],"face":[76],"applied":[79],"pronounced":[86],"gaps":[88],"and":[89,115,131,138,145,162,175,215],"error":[90],"unawareness":[91],"problems.":[92],"In":[93],"work,":[95],"we":[96,119,148],"propose":[97],"novel":[99],"error-aware":[100],"framework":[103],"imagery":[107],"semantic":[108,152,160],"segmentation,":[109],"called":[110],"EasySeg,":[111],"via":[112],"interactive":[113,130,151,163],"learning.":[117],"Firstly,":[118],"introduce":[120,149],"point-level":[122,170],"labeling":[123,223],"strategy,":[124],"named":[125],"\"See-First-Ask-Later\"":[126],"(SFAL),":[127],"combining":[128],"both":[129],"manners,":[134],"allowing":[135],"obvious":[136],"errors":[137],"information-rich":[139],"pixels":[140],"be":[142],"annotated":[143],"easily":[144],"efficiently.":[146],"Then,":[147],"an":[150],"network":[154],"(ISS-Net),":[155],"can":[157],"perform":[158],"automatic":[159],"refinement.":[164],"Based":[165],"the":[167,198],"acquired":[168],"target":[169],"labels,":[171],"ISS-Net":[172],"generates":[173],"dense":[174],"accurate":[176],"pseudo-labels":[177],"enhance":[179],"through":[183],"retraining":[184],"with":[185,221],"consistency":[186],"regularization.":[187],"Comprehensive":[188],"experiments":[189],"two":[191],"tasks":[192],"demonstrate":[193],"that":[194],"our":[195],"method":[196],"outperforms":[197],"state-of-the-art":[199],"terms":[205],"overall":[207],"accuracy":[208,211],"(OA),":[209],"mean":[210,216],"(MA),":[212],"F1":[213],"score,":[214],"Intersection":[217],"Union":[219],"(mIoU)":[220],"lower":[222],"costs,":[224],"even":[225],"surpassing":[226],"some":[227],"The":[231],"source":[232],"code":[233],"EasySeg":[235],"is":[236],"freely":[237],"available":[238],"at":[239],"https://github.com/Yangliangzhe/EasySeg.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}