{"id":"https://openalex.org/W4400877991","doi":"https://doi.org/10.1109/tgrs.2024.3432397","title":"Causality-Guided Stepwise Intervention and Reweighting for Remote Sensing Image Semantic Segmentation","display_name":"Causality-Guided Stepwise Intervention and Reweighting for Remote Sensing Image Semantic Segmentation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400877991","doi":"https://doi.org/10.1109/tgrs.2024.3432397"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3432397","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tgrs.2024.3432397","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/A5018742600","display_name":"Shuting Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuting Shi","raw_affiliation_strings":["Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-8688-848X","affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106596973","display_name":"LI Bao-hong","orcid":"https://orcid.org/0000-0002-3222-002X"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baohong Li","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3222-002X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106596914","display_name":"Laifu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laifu Zhang","raw_affiliation_strings":["Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-7982-1407","affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041727387","display_name":"Kun Kuang","orcid":"https://orcid.org/0000-0001-7024-9790"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Kuang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7024-9790","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085580167","display_name":"Sensen Wu","orcid":"https://orcid.org/0000-0001-9322-0149"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sensen Wu","raw_affiliation_strings":["Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9322-0149","affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018040823","display_name":"Tian Feng","orcid":"https://orcid.org/0000-0001-9691-3266"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Feng","raw_affiliation_strings":["School of Software Technology, Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9691-3266","affiliations":[{"raw_affiliation_string":"School of Software Technology, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041395379","display_name":"Yiming Yan","orcid":"https://orcid.org/0000-0003-0751-7726"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yiming Yan","raw_affiliation_strings":["Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069094261","display_name":"Zhenhong Du","orcid":"https://orcid.org/0000-0001-9449-0415"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenhong Du","raw_affiliation_strings":["Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9449-0415","affiliations":[{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8175,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72439058,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987000226974487,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987000226974487,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9966999888420105,"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":0.7113833427429199},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6360614895820618},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5601541996002197},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5529138445854187},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5005908012390137},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.4854333996772766},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.485029399394989},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4762554168701172},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3295522928237915},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.17571741342544556}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7113833427429199},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6360614895820618},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5601541996002197},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5529138445854187},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5005908012390137},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.4854333996772766},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.485029399394989},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4762554168701172},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3295522928237915},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.17571741342544556},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3432397","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/tgrs.2024.3432397","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":0.41999998688697815,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3656585794","display_name":null,"funder_award_id":"2022FZZX01-05","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4205730269","display_name":null,"funder_award_id":"226-2024-00124","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4562286584","display_name":null,"funder_award_id":"42225605","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5879540094","display_name":null,"funder_award_id":"42001323","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/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W2037227137","https://openalex.org/W2088805832","https://openalex.org/W2108598243","https://openalex.org/W2143891888","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2345125502","https://openalex.org/W2412782625","https://openalex.org/W2463983882","https://openalex.org/W2507296351","https://openalex.org/W2561196672","https://openalex.org/W2630837129","https://openalex.org/W2787091153","https://openalex.org/W2804935296","https://openalex.org/W2807974043","https://openalex.org/W2883105896","https://openalex.org/W2893363236","https://openalex.org/W2916798096","https://openalex.org/W2962858109","https://openalex.org/W2963881378","https://openalex.org/W2963995737","https://openalex.org/W2964254462","https://openalex.org/W2979273157","https://openalex.org/W2981413347","https://openalex.org/W2996290406","https://openalex.org/W3008439211","https://openalex.org/W3009551409","https://openalex.org/W3035512383","https://openalex.org/W3108975329","https://openalex.org/W3124658416","https://openalex.org/W3131500599","https://openalex.org/W3135196696","https://openalex.org/W3170841864","https://openalex.org/W4205138939","https://openalex.org/W4210276931","https://openalex.org/W4213244466","https://openalex.org/W4213447687","https://openalex.org/W4214893857","https://openalex.org/W4280568747","https://openalex.org/W4288325606","https://openalex.org/W4311088167","https://openalex.org/W4312443924","https://openalex.org/W4312688875","https://openalex.org/W4312815172","https://openalex.org/W4318681845","https://openalex.org/W4324387399","https://openalex.org/W4385803813","https://openalex.org/W4386076397","https://openalex.org/W4387415454","https://openalex.org/W4390874575","https://openalex.org/W4394758452","https://openalex.org/W6637373629","https://openalex.org/W6682132143","https://openalex.org/W6711306941","https://openalex.org/W6729580568","https://openalex.org/W6739095351","https://openalex.org/W6739696289","https://openalex.org/W6747514548","https://openalex.org/W6755223120","https://openalex.org/W6762718338","https://openalex.org/W6782868315","https://openalex.org/W6784163774","https://openalex.org/W6797399245","https://openalex.org/W6797784111","https://openalex.org/W6798837711","https://openalex.org/W6842806116","https://openalex.org/W6847417593","https://openalex.org/W6851543690","https://openalex.org/W6862386595"],"related_works":["https://openalex.org/W2081494945","https://openalex.org/W2389053294","https://openalex.org/W1970893504","https://openalex.org/W4312071518","https://openalex.org/W2901208600","https://openalex.org/W1677090476","https://openalex.org/W830525666","https://openalex.org/W2330229995","https://openalex.org/W3014724311","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,168,206],"is":[2],"one":[3],"of":[4,28,52,96,128,169,183,217],"the":[5,25,50,62,66,71,97,105,119,129,136,149,154,159,212,218],"most":[6],"significant":[7],"tasks":[8],"in":[9],"remote":[10],"sensing":[11],"(RS)":[12],"image":[13],"interpretation,":[14],"which":[15],"focuses":[16],"on":[17,135,190],"learning":[18,37],"global":[19,42],"and":[20,43,70,114,117,132,143,157,186,214],"local":[21,44],"information":[22,123],"to":[23,40,55,61,73,80,85,162,203],"infer":[24],"semantic":[26,57,167,205],"label":[27],"each":[29],"pixel.":[30],"Previous":[31],"studies":[32],"devise":[33],"encoder-decoder":[34,204],"structured":[35],"deep":[36],"(DL)":[38],"models":[39,78,110,207],"extract":[41],"features":[45,83,107],"from":[46,100,108,112,174],"RS":[47,86,170,195],"images":[48,171],"with":[49],"help":[51],"pretraining":[53,69,155],"knowledge":[54,156],"predict":[56],"labels.":[58],"However,":[59],"due":[60],"common":[63],"heterogeneity":[64],"between":[65],"data":[67,72],"for":[68],"be":[74],"semantically":[75],"segmented,":[76],"these":[77],"fail":[79],"learn":[81,163],"general":[82,122,164],"appropriate":[84],"datasets.":[87,196],"In":[88],"this":[89],"article,":[90],"we":[91,139,177],"propose":[92,140],"a":[93,101,179],"novel":[94],"formulation":[95],"above":[98,137],"problem":[99],"causal":[102],"perspective,":[103],"where":[104],"learned":[106],"pretrained":[109],"result":[111],"causality":[113],"spurious":[115],"correlations,":[116],"only":[118],"former":[120],"carries":[121],"that":[124,200],"remains":[125],"invariant":[126],"regardless":[127],"exact":[130],"task":[131],"dataset.":[133],"Based":[134],"formulation,":[138],"stepwise":[141],"intervention":[142],"reweighting":[144],"(SIR).":[145],"It":[146],"can":[147],"reduce":[148],"confounding":[150],"bias":[151],"introduced":[152],"by":[153],"improve":[158],"model\u2019s":[160],"ability":[161],"features,":[165],"making":[166],"benefit":[172],"more":[173],"pretraining.":[175],"Besides,":[176],"conduct":[178,187],"detailed":[180],"theoretical":[181],"analysis":[182],"our":[184],"methods":[185],"extensive":[188],"experiments":[189],"two":[191],"widely":[192],"used":[193],"public":[194],"Experimental":[197],"results":[198],"demonstrate":[199],"applying":[201],"SIR":[202],"achieves":[208],"performance":[209],"improvements,":[210],"proving":[211],"effectiveness":[213],"application":[215],"values":[216],"proposed":[219],"method.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}