{"id":"https://openalex.org/W4406209012","doi":"https://doi.org/10.1109/lgrs.2025.3527473","title":"Causal Invariant Representation Learning Based on Style Intervention Identity Regularization for Remote Sensing Image","display_name":"Causal Invariant Representation Learning Based on Style Intervention Identity Regularization for Remote Sensing Image","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406209012","doi":"https://doi.org/10.1109/lgrs.2025.3527473"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3527473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3527473","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5103017648","display_name":"Yunsheng Zhang","orcid":"https://orcid.org/0000-0002-2779-2015"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunsheng Zhang","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-2779-2015","affiliations":[{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073889455","display_name":"Fanfan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fanfan Liu","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104946285","display_name":"Jia Zhang","orcid":"https://orcid.org/0009-0005-6061-5386"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Zhang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China","China Academy of Aerospace Science and Innovation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"China Academy of Aerospace Science and Innovation, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100398353","display_name":"Haifeng Li","orcid":"https://orcid.org/0000-0003-1173-6593"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haifeng Li","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-1173-6593","affiliations":[{"raw_affiliation_string":"School of Geosciences and Info-Physics, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00648705,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976999759674072,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.995199978351593,"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":0.5788922905921936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5637764930725098},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4740138649940491},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4372588098049164},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40118756890296936},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3787696361541748},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27647721767425537}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5788922905921936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5637764930725098},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4740138649940491},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4372588098049164},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40118756890296936},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3787696361541748},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27647721767425537},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3527473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3527473","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G1895075832","display_name":null,"funder_award_id":"42271481","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2143891888","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2804199516","https://openalex.org/W3009561768","https://openalex.org/W3110908156","https://openalex.org/W3121370741","https://openalex.org/W3130231677","https://openalex.org/W3135367836","https://openalex.org/W3216352822","https://openalex.org/W4210642697","https://openalex.org/W4285128126","https://openalex.org/W4285168619","https://openalex.org/W4287640040","https://openalex.org/W4293327156","https://openalex.org/W4312309687","https://openalex.org/W4312740349","https://openalex.org/W4379033857","https://openalex.org/W4386213542","https://openalex.org/W4388936930","https://openalex.org/W4398139373","https://openalex.org/W6637373629","https://openalex.org/W6774670964","https://openalex.org/W6783713337","https://openalex.org/W6784392697","https://openalex.org/W6842958722"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"An":[0],"intelligent":[1],"understanding":[2],"model":[3,156],"of":[4,14,26,41,71,78,82,100,122,167],"a":[5,131,154,201],"remote":[6,20,84,132,168,190,224],"sensing":[7,21,85,133,169,191,225],"image":[8,86],"will":[9],"present":[10],"different":[11,197],"visual":[12],"representations":[13,213,237],"the":[15,19,24,38,42,58,68,72,75,83,97,101,112,120,146,165,184,205],"same":[16],"object":[17,81],"in":[18],"image,":[22],"under":[23,62,253],"interference":[25,121],"offset":[27],"factors,":[28],"such":[29],"as":[30,159,183],"weather":[31],"and":[32,66,93,107,109,125],"season.":[33],"This":[34,128,187],"variability":[35],"adversely":[36],"affects":[37],"generalization":[39,60],"ability":[40,61],"model;":[43],"therefore,":[44],"an":[45,160],"open":[46],"challenge":[47],"is":[48,87,96,105,111,116,126,157,177,259],"how":[49],"to":[50,119,163,199],"learn":[51],"invariant":[52,211,235],"features.":[53],"These":[54],"features":[55],"can":[56],"maintain":[57],"model\u2019s":[59],"various":[63],"imaging":[64],"conditions":[65],"given":[67],"spatiotemporal":[69],"heterogeneity":[70],"object.":[73],"From":[74],"causal":[76,98],"point":[77],"view,":[79],"each":[80],"decomposed":[88],"into":[89],"two":[90],"parts,":[91],"content":[92,95,195,212,236],"style;":[94],"variable":[99],"target":[102,206],"task,":[103,207],"which":[104,115],"robust":[106],"stable,":[108],"style":[110,140,150,166,173,216],"noncausal":[113],"variable,":[114],"more":[117],"susceptible":[118],"bias":[123],"factors":[124],"volatile.":[127],"paper":[129],"proposes":[130],"imagery":[134],"invariance":[135],"representation":[136,241],"method":[137],"based":[138,152,244],"on":[139,153,204,222,245],"intervention":[141,161,174],"identity":[142,175],"regularization":[143,176],"(ICRNet).":[144],"Within":[145],"contrastive":[147],"learning":[148,210,242],"framework,":[149],"transformation":[151],"diffusion":[155],"introduced":[158],"factor":[162],"modify":[164],"images.":[170],"In":[171],"addition,":[172],"designed,":[178],"employing":[179],"symmetric":[180],"JS":[181],"divergence":[182],"similarity":[185],"measure.":[186],"approach":[188],"forces":[189],"images":[192],"with":[193],"identical":[194],"but":[196],"styles":[198],"have":[200],"similar":[202],"impact":[203],"thereby":[208],"enabling":[209],"while":[214],"ignoring":[215],"representations.":[217],"The":[218,229,256],"experiments":[219],"were":[220],"conducted":[221],"three":[223],"semantic":[226],"segmentation":[227],"datasets.":[228],"results":[230],"reveal":[231],"that":[232],"ICRNet":[233,249],"learns":[234],"better":[238],"than":[239],"alternative":[240],"approaches":[243],"contrast":[246],"learning.":[247],"Additionally,":[248],"exhibits":[250],"higher":[251],"generalizability":[252],"seasonal":[254],"bias.":[255],"source":[257],"code":[258],"available":[260],"at":[261],"https://github.com/GeoX-Lab/ICRNet.":[262]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
