{"id":"https://openalex.org/W4313063910","doi":"https://doi.org/10.1109/tgrs.2022.3225589","title":"Attention-Based Dynamic Alignment and Dynamic Distribution Adaptation for Remote Sensing Cross-Domain Scene Classification","display_name":"Attention-Based Dynamic Alignment and Dynamic Distribution Adaptation for Remote Sensing Cross-Domain Scene Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4313063910","doi":"https://doi.org/10.1109/tgrs.2022.3225589"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3225589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3225589","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/A5100669592","display_name":"Cong Yang","orcid":"https://orcid.org/0000-0001-5933-0950"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Yang","raw_affiliation_strings":["School of Geophysics and Geomatics, China University of Geosciences, Wuhan, China","Hubei Luojia Laboratory, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geophysics and Geomatics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"Hubei Luojia Laboratory, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084097095","display_name":"Yanni Dong","orcid":"https://orcid.org/0000-0003-0592-7887"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanni Dong","raw_affiliation_strings":["School of Geophysics and Geomatics, China University of Geosciences, Wuhan, China","Hubei Luojia Laboratory, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-0592-7887","affiliations":[{"raw_affiliation_string":"School of Geophysics and Geomatics, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"Hubei Luojia Laboratory, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060042752","display_name":"Bo Du","orcid":"https://orcid.org/0000-0002-0059-8458"},"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":"Bo Du","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0059-8458","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100673818","display_name":"Liangpei Zhang","orcid":"https://orcid.org/0000-0001-6890-3650"},"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"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangpei Zhang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6890-3650","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0195,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.92298065,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"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":0.9968000054359436,"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":0.9968000054359436,"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":0.984499990940094,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8065717220306396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7926434874534607},{"id":"https://openalex.org/keywords/marginal-distribution","display_name":"Marginal distribution","score":0.6244702339172363},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.6214278340339661},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6210268139839172},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5855737924575806},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5161226987838745},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5152721405029297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4972741901874542},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4948403239250183},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.45499473810195923},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4465109705924988},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4395866394042969},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41247978806495667},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.41145309805870056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39027976989746094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14479750394821167},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09603947401046753}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8065717220306396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7926434874534607},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.6244702339172363},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.6214278340339661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6210268139839172},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5855737924575806},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5161226987838745},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5152721405029297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4972741901874542},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4948403239250183},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.45499473810195923},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4465109705924988},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4395866394042969},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41247978806495667},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41145309805870056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39027976989746094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14479750394821167},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09603947401046753},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3225589","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3225589","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G6175404752","display_name":null,"funder_award_id":"62171417","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G949604467","display_name":null,"funder_award_id":"62222116","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":80,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1882958252","https://openalex.org/W1980038761","https://openalex.org/W2096943734","https://openalex.org/W2098676252","https://openalex.org/W2115403315","https://openalex.org/W2120149881","https://openalex.org/W2156387975","https://openalex.org/W2159291411","https://openalex.org/W2163605009","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2240757205","https://openalex.org/W2515866431","https://openalex.org/W2592962403","https://openalex.org/W2610614780","https://openalex.org/W2616287544","https://openalex.org/W2621526417","https://openalex.org/W2752386593","https://openalex.org/W2752782242","https://openalex.org/W2795155917","https://openalex.org/W2884585870","https://openalex.org/W2884771968","https://openalex.org/W2899198451","https://openalex.org/W2904706552","https://openalex.org/W2917187459","https://openalex.org/W2938486422","https://openalex.org/W2948959975","https://openalex.org/W2962858109","https://openalex.org/W2963168418","https://openalex.org/W2963214104","https://openalex.org/W2963217615","https://openalex.org/W2963275094","https://openalex.org/W2964278684","https://openalex.org/W2964288524","https://openalex.org/W2968584961","https://openalex.org/W2973777195","https://openalex.org/W2974291863","https://openalex.org/W2974373385","https://openalex.org/W2974770574","https://openalex.org/W2978573218","https://openalex.org/W2981413347","https://openalex.org/W2982671374","https://openalex.org/W2989738275","https://openalex.org/W2991405316","https://openalex.org/W2998666297","https://openalex.org/W3004205097","https://openalex.org/W3009072794","https://openalex.org/W3017075957","https://openalex.org/W3021632667","https://openalex.org/W3023931079","https://openalex.org/W3035576098","https://openalex.org/W3105577662","https://openalex.org/W3112870575","https://openalex.org/W3118513496","https://openalex.org/W3119205652","https://openalex.org/W3120800376","https://openalex.org/W3123352549","https://openalex.org/W3124219615","https://openalex.org/W3136251366","https://openalex.org/W3174089775","https://openalex.org/W3182963544","https://openalex.org/W3194997359","https://openalex.org/W3202194958","https://openalex.org/W4212963965","https://openalex.org/W4214666412","https://openalex.org/W4229457118","https://openalex.org/W4297810817","https://openalex.org/W4312762953","https://openalex.org/W6631190155","https://openalex.org/W6639480849","https://openalex.org/W6682889407","https://openalex.org/W6683633756","https://openalex.org/W6684191040","https://openalex.org/W6688325169","https://openalex.org/W6713955831","https://openalex.org/W6734335776","https://openalex.org/W6743837088","https://openalex.org/W6750109254","https://openalex.org/W6753038380"],"related_works":["https://openalex.org/W2497288182","https://openalex.org/W4243126796","https://openalex.org/W12046094","https://openalex.org/W4249162344","https://openalex.org/W162901985","https://openalex.org/W2952129880","https://openalex.org/W4294642871","https://openalex.org/W4234449911","https://openalex.org/W4237297272","https://openalex.org/W259963716"],"abstract_inverted_index":{"Due":[0],"to":[1,25,31,61,78,136,194],"the":[2,28,33,44,74,80,87,96,101,109,120,139,147,159,168,177,195,203,207],"lack":[3],"of":[4,12,89,112,150,162],"high-quality":[5],"labeled":[6],"data":[7,40],"and":[8,48,83,114,130,156,164,205],"poor":[9],"generalization":[10],"ability":[11],"supervised":[13],"models":[14],"in":[15,92,153,202,210],"remote":[16],"sensing":[17],"scene":[18,21],"classification,":[19],"cross-domain":[20],"classification":[22],"is":[23,38,192],"proposed":[24,60,190],"better":[26,137],"utilize":[27],"existing":[29,67,102],"knowledge":[30,173],"classify":[32],"unlabeled":[34],"data.":[35],"Since":[36],"there":[37],"a":[39,125],"distribution":[41,64,82,141],"difference":[42],"between":[43,142],"training":[45],"(source":[46],"domain)":[47,51],"test":[49],"(target":[50],"set,":[52],"many":[53],"deep":[54,68,198],"domain":[55,69,103,199],"adaptation":[56,70,104,200],"methods":[57,71,105,201],"have":[58],"been":[59],"reduce":[62],"such":[63],"discrepancy.":[65],"However,":[66],"usually":[72],"use":[73],"discrepancy":[75],"metric":[76],"function":[77],"align":[79,138],"marginal":[81,113,140,163],"do":[84],"not":[85],"consider":[86],"effect":[88],"each":[90,151],"sample":[91,152],"different":[93,143,154],"domains":[94,155],"on":[95],"network":[97],"weights.":[98],"In":[99],"addition,":[100],"cannot":[106],"adaptively":[107],"balance":[108,158],"relative":[110,160],"importance":[111,161],"conditional":[115,165],"distributions":[116,144],"well.":[117],"To":[118],"overcome":[119],"above":[121],"shortcomings,":[122],"we":[123],"propose":[124],"novel":[126],"Attention-based":[127],"Dynamic":[128,131],"Alignment":[129],"Distribution":[132],"Adaptation":[133],"(ADA-DDA)":[134],"method":[135,191],"by":[145,212],"calculating":[146],"dynamic":[148],"weights":[149],"dynamically":[157],"distributions.":[166],"Moreover,":[167],"attention":[169],"mechanism":[170],"enables":[171],"purposeful":[172],"transfer,":[174],"so":[175],"that":[176,188],"extracted":[178],"features":[179],"can":[180],"be":[181],"highly":[182],"discriminative.":[183],"The":[184],"experimental":[185],"results":[186],"demonstrate":[187],"our":[189],"superior":[193],"other":[196],"state-of-the-art":[197],"comparison,":[204],"outperforms":[206],"second":[208],"place":[209],"accuracy":[211],"5.36%.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
