{"id":"https://openalex.org/W4403599516","doi":"https://doi.org/10.1109/tgrs.2024.3481875","title":"Domain-Incremental Learning for Remote Sensing Semantic Segmentation With Multifeature Constraints in Graph Space","display_name":"Domain-Incremental Learning for Remote Sensing Semantic Segmentation With Multifeature Constraints in Graph Space","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403599516","doi":"https://doi.org/10.1109/tgrs.2024.3481875"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3481875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3481875","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/A5023165108","display_name":"Wubiao Huang","orcid":"https://orcid.org/0000-0003-2856-9859"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wubiao Huang","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053536338","display_name":"Mingtao Ding","orcid":"https://orcid.org/0000-0003-1210-9188"},"institutions":[{"id":"https://openalex.org/I4210115513","display_name":"Xi\u2019an University","ror":"https://ror.org/01zzmf129","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115513"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingtao Ding","raw_affiliation_strings":["College of Geological Engineering and Geomatics, Chang&#x2019;an University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"College of Geological Engineering and Geomatics, Chang&#x2019;an University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210115513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101966846","display_name":"Fei Deng","orcid":"https://orcid.org/0000-0003-0886-4324"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Deng","raw_affiliation_strings":["School of Geodesy and Geomatics, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Geodesy and Geomatics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023165108"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":3.2635,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.93108235,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"15"},"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":0.9750000238418579,"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":0.9750000238418579,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7694976329803467},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5681011080741882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5508015751838684},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5406915545463562},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5236958265304565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48938149213790894},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.44032543897628784},{"id":"https://openalex.org/keywords/data-space","display_name":"Data space","score":0.41664737462997437},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41628628969192505},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3959009647369385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34101563692092896},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20126935839653015},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12957781553268433},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11543050408363342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7694976329803467},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5681011080741882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5508015751838684},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5406915545463562},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5236958265304565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48938149213790894},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.44032543897628784},{"id":"https://openalex.org/C2988382989","wikidata":"https://www.wikidata.org/wiki/Q370685","display_name":"Data space","level":2,"score":0.41664737462997437},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41628628969192505},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3959009647369385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34101563692092896},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20126935839653015},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12957781553268433},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11543050408363342},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3481875","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3481875","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":[{"id":"https://openalex.org/G6724052967","display_name":null,"funder_award_id":"42374027","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2395611524","https://openalex.org/W2473930607","https://openalex.org/W2560023338","https://openalex.org/W2560647685","https://openalex.org/W2787091153","https://openalex.org/W2895340641","https://openalex.org/W2910628332","https://openalex.org/W2940726923","https://openalex.org/W2955058313","https://openalex.org/W2963319519","https://openalex.org/W2981689412","https://openalex.org/W3031478966","https://openalex.org/W3035358681","https://openalex.org/W3035526186","https://openalex.org/W3046023298","https://openalex.org/W3081064176","https://openalex.org/W3107591966","https://openalex.org/W3121873598","https://openalex.org/W3150112631","https://openalex.org/W3152475769","https://openalex.org/W3153987619","https://openalex.org/W3165935199","https://openalex.org/W3168256178","https://openalex.org/W3171888599","https://openalex.org/W3207978380","https://openalex.org/W3208194557","https://openalex.org/W3208750293","https://openalex.org/W4205365435","https://openalex.org/W4224048116","https://openalex.org/W4226183927","https://openalex.org/W4283450732","https://openalex.org/W4302775088","https://openalex.org/W4312210066","https://openalex.org/W4313420531","https://openalex.org/W4321617226","https://openalex.org/W4323897048","https://openalex.org/W4362582463","https://openalex.org/W4376275515","https://openalex.org/W4383337348","https://openalex.org/W4384080551","https://openalex.org/W4385062313","https://openalex.org/W4386127154","https://openalex.org/W4388157208","https://openalex.org/W4389104786","https://openalex.org/W4389301963","https://openalex.org/W4390488981","https://openalex.org/W4390872751","https://openalex.org/W4391249108","https://openalex.org/W4391661515","https://openalex.org/W4392173735","https://openalex.org/W4392806026","https://openalex.org/W4393906060","https://openalex.org/W4394008640","https://openalex.org/W4402667899","https://openalex.org/W6726873649","https://openalex.org/W6755950020","https://openalex.org/W6767688279","https://openalex.org/W6799579066"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W4248700453","https://openalex.org/W2149773306","https://openalex.org/W76341530","https://openalex.org/W1597543867","https://openalex.org/W1717930517","https://openalex.org/W2148200517","https://openalex.org/W2145661674","https://openalex.org/W4315703132"],"abstract_inverted_index":{"The":[0,154],"use":[1,94],"of":[2,95,110],"deep":[3,72],"learning":[4,61,73],"techniques":[5],"for":[6,33],"semantic":[7,34,113],"segmentation":[8,35,114],"in":[9,77,118,148],"remote":[10,18,111],"sensing":[11,112],"has":[12],"been":[13],"increasingly":[14],"prevalent.":[15],"Effectively":[16],"modeling":[17],"contextual":[19],"information":[20,91],"and":[21,50,88,99,133,144,151],"integrating":[22],"high-level":[23],"abstract":[24],"features":[25,29],"with":[26,115],"low-level":[27],"spatial":[28],"are":[30],"critical":[31],"challenges":[32,41],"tasks.":[36,153],"This":[37,79],"article":[38],"addresses":[39],"these":[40],"by":[42],"constructing":[43],"a":[44,51,58,82,107],"graph":[45,119],"space":[46,120],"reasoning":[47],"(GSR)":[48],"module":[49],"dual-channel":[52],"cross-attention":[53],"upsampling":[54],"(DCAU)":[55],"module.":[56],"Meanwhile,":[57],"new":[59,90,108],"domain-incremental":[60],"(DIL)":[62],"framework":[63,80,122],"is":[64,75,123,156],"designed":[65],"to":[66],"alleviate":[67],"catastrophic":[68],"forgetting":[69],"when":[70],"the":[71,93,131,138],"model":[74],"used":[76],"cross-domain.":[78],"makes":[81],"balance":[83],"between":[84],"retaining":[85],"prior":[86],"knowledge":[87],"acquiring":[89],"through":[92],"frozen":[96],"feature":[97],"layers":[98],"multifeature":[100,116],"joint":[101],"loss":[102],"optimization.":[103],"Based":[104],"on":[105,130],"this,":[106],"DIL":[109],"constraints":[117],"(GSMF-RS-DIL)":[121],"proposed.":[124],"Extensive":[125],"experiments,":[126],"including":[127],"ablation":[128],"experiments":[129],"ISPRS":[132],"LoveDA":[134],"datasets,":[135],"demonstrate":[136],"that":[137],"proposed":[139],"method":[140],"achieves":[141],"superior":[142],"performance":[143],"optimal":[145],"computational":[146],"efficiency":[147],"both":[149],"single-domain":[150],"cross-domain":[152],"code":[155],"publicly":[157],"available":[158],"at":[159],"<uri":[160],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[161],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/Huang</uri>":[162],"WBill/GSMF-RS-DIL.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
