{"id":"https://openalex.org/W4313270784","doi":"https://doi.org/10.1109/tgrs.2022.3233133","title":"PCLUDA: A Pseudo-Label Consistency Learning- Based Unsupervised Domain Adaptation Method for Cross-Domain Optical Remote Sensing Image Retrieval","display_name":"PCLUDA: A Pseudo-Label Consistency Learning- Based Unsupervised Domain Adaptation Method for Cross-Domain Optical Remote Sensing Image Retrieval","publication_year":2022,"publication_date":"2022-12-29","ids":{"openalex":"https://openalex.org/W4313270784","doi":"https://doi.org/10.1109/tgrs.2022.3233133"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3233133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233133","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/A5058638373","display_name":"Dongyang Hou","orcid":"https://orcid.org/0000-0002-1156-9353"},"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":"Dongyang Hou","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-1156-9353","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/A5100440549","display_name":"Siyuan Wang","orcid":"https://orcid.org/0000-0002-5506-7451"},"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":"Siyuan Wang","raw_affiliation_strings":["School of Geosciences and Info-Physics, Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-5506-7451","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/A5003925465","display_name":"Xueqing Tian","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":"Xueqing Tian","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":"last","author":{"id":"https://openalex.org/A5055460928","display_name":"Huaqiao Xing","orcid":"https://orcid.org/0000-0002-8748-1729"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaqiao Xing","raw_affiliation_strings":["School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-8748-1729","affiliations":[{"raw_affiliation_string":"School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China","institution_ids":["https://openalex.org/I44445938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2195,"currency":"USD","value_usd":2195},"apc_paid":null,"fwci":3.843,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.94063978,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"14"},"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":0.9979000091552734,"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":0.9979000091552734,"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":0.9959999918937683,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.994700014591217,"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":0.7693979740142822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5601375102996826},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5422762632369995},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.48680898547172546},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47873613238334656},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.46906495094299316},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4350779056549072},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4182482957839966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39974460005760193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36899304389953613},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35681164264678955},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15477293729782104},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.0894254744052887}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7693979740142822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5601375102996826},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5422762632369995},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.48680898547172546},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47873613238334656},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.46906495094299316},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4350779056549072},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4182482957839966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39974460005760193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36899304389953613},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35681164264678955},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15477293729782104},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0894254744052887},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3233133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233133","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":0.75,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5862799222","display_name":null,"funder_award_id":"42171457","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G95363034","display_name":null,"funder_award_id":"2021JJ40721","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1731081199","https://openalex.org/W1980038761","https://openalex.org/W2121765205","https://openalex.org/W2159291411","https://openalex.org/W2183341477","https://openalex.org/W2194600502","https://openalex.org/W2194775991","https://openalex.org/W2479919622","https://openalex.org/W2515866431","https://openalex.org/W2592962403","https://openalex.org/W2593768305","https://openalex.org/W2626107033","https://openalex.org/W2741346264","https://openalex.org/W2799087793","https://openalex.org/W2808376087","https://openalex.org/W2883105896","https://openalex.org/W2883780447","https://openalex.org/W2909487414","https://openalex.org/W2917187459","https://openalex.org/W2919263357","https://openalex.org/W2931053602","https://openalex.org/W2937019265","https://openalex.org/W2946812986","https://openalex.org/W2955950606","https://openalex.org/W2963168418","https://openalex.org/W2963446712","https://openalex.org/W2963449430","https://openalex.org/W2964057616","https://openalex.org/W2964278684","https://openalex.org/W2968945589","https://openalex.org/W2982083293","https://openalex.org/W2987823303","https://openalex.org/W2991488782","https://openalex.org/W2998115938","https://openalex.org/W3001197829","https://openalex.org/W3004827100","https://openalex.org/W3016719260","https://openalex.org/W3035682985","https://openalex.org/W3042481550","https://openalex.org/W3080167796","https://openalex.org/W3093905312","https://openalex.org/W3105079884","https://openalex.org/W3105577662","https://openalex.org/W3109093849","https://openalex.org/W3132184743","https://openalex.org/W3134552197","https://openalex.org/W3159249290","https://openalex.org/W3176663948","https://openalex.org/W3181227279","https://openalex.org/W3184438950","https://openalex.org/W3198422076","https://openalex.org/W3203482237","https://openalex.org/W3205693451","https://openalex.org/W3207169751","https://openalex.org/W3212904394","https://openalex.org/W4213440574","https://openalex.org/W4221086150","https://openalex.org/W4223540136","https://openalex.org/W4226172762","https://openalex.org/W4296501431","https://openalex.org/W4300903698","https://openalex.org/W4320013936","https://openalex.org/W6637373629","https://openalex.org/W6683633756","https://openalex.org/W6713955831","https://openalex.org/W6745986955","https://openalex.org/W6751395999","https://openalex.org/W6761139768","https://openalex.org/W6763066025","https://openalex.org/W6773005947"],"related_works":["https://openalex.org/W4308262314","https://openalex.org/W4382286161","https://openalex.org/W2895583656","https://openalex.org/W2960456850","https://openalex.org/W3021430260","https://openalex.org/W4281645081","https://openalex.org/W2946016983","https://openalex.org/W4312200629","https://openalex.org/W2901026139","https://openalex.org/W4301607095"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,37,47,121,213,231],"deep":[3,235],"learning":[4,236],"have":[5,62],"dramatically":[6],"improved":[7],"the":[8,18,67,70,81,95,119,125,143,149],"performance":[9],"of":[10,21,80,168,234],"content-based":[11],"remote":[12,59],"sensing":[13,60],"image":[14],"retrieval":[15,48,97,198,202,229],"(CBRSIR)":[16],"with":[17,173,200,208],"same":[19],"distribution":[20,84,123],"training":[22],"set":[23,28],"(source":[24],"domain)":[25],"and":[26,128,136,242],"test":[27],"(target":[29],"domain).":[30],"In":[31,99],"fact,":[32],"their":[33],"distributions":[34],"are":[35,177],"inconsistent":[36],"most":[38],"cases,":[39],"which":[40],"can":[41,225],"lead":[42],"to":[43,65,93,148,159,185],"a":[44,102,133],"dramatic":[45],"decrease":[46],"performance.":[49,98],"Currently,":[50],"some":[51],"unsupervised":[52,72,106],"domain":[53,127],"adaptation":[54],"(DA)":[55],"methods":[56,74],"for":[57,112],"other":[58,218],"applications":[61],"been":[63],"proposed":[64,111],"eliminate":[66],"inconsistency.":[68],"However,":[69],"current":[71],"DA":[73,107,187,211],"do":[75],"not":[76],"make":[77],"full":[78],"use":[79],"target":[82,126,144],"domain\u2019s":[83,145],"characteristics":[85],"when":[86],"delineating":[87],"its":[88,129],"decision":[89,146],"boundary.":[90],"This":[91],"tends":[92],"degrade":[94],"cross-domain":[96,113,171,175,215],"this":[100],"article,":[101],"pseudo-label":[103,134],"consistency":[104,137],"learning-based":[105],"method":[108,117,195],"(PCLUDA)":[109],"is":[110,157],"CBRSIR.":[114],"Our":[115],"PCLUDA":[116,194,224],"minimizes":[118],"difference":[120],"probability":[122],"between":[124],"perturbed":[130],"output":[131],"by":[132,141,164,205],"self-training":[135],"regularization":[138],"strategy,":[139],"followed":[140],"adjusting":[142],"boundaries":[147],"low-density":[150],"region.":[151],"Besides,":[152],"minimize":[153],"class":[154],"confusion":[155],"(MCC)":[156],"introduced":[158],"reduce":[160],"negative":[161],"transfer":[162],"caused":[163],"large":[165],"intraclass":[166],"variance":[167],"RSIs.":[169],"Two":[170],"datasets":[172,184],"12":[174],"scenarios":[176],"constructed":[178],"based":[179],"on":[180],"six":[181],"open":[182],"access":[183],"measure":[186],"methods.":[188],"Experimental":[189],"results":[190,220],"show":[191],"that":[192,222],"our":[193,223],"achieves":[196],"superior":[197],"performances":[199,230],"average":[201],"precision":[203],"improvement":[204],"4.9%\u201332.3%":[206],"compared":[207],"eight":[209],"state-of-the-art":[210],"approaches":[212],"complex":[214],"scenarios.":[216],"Furthermore,":[217],"experimental":[219],"indicate":[221],"also":[226],"reach":[227],"optimal":[228],"different":[232],"kinds":[233],"networks":[237,245],"[i.e.,":[238],"vision":[239],"transformer":[240],"(ViT)":[241],"convolutional":[243],"neural":[244],"(CNNs)].":[246]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":6}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
