{"id":"https://openalex.org/W4313525856","doi":"https://doi.org/10.1109/tgrs.2022.3233885","title":"Language-Aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification","display_name":"Language-Aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313525856","doi":"https://doi.org/10.1109/tgrs.2022.3233885"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3233885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233885","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/A5101769560","display_name":"Yuxiang Zhang","orcid":"https://orcid.org/0000-0001-5228-3215"},"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":true,"raw_author_name":"Yuxiang Zhang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442192","display_name":"Mengmeng Zhang","orcid":"https://orcid.org/0000-0002-5724-9785"},"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":"Mengmeng Zhang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"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":"Wei Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328245","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0001-8897-9476"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["Department of Chemistry, The University of Hong Kong, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Department of Chemistry, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067803447","display_name":"Ran Tao","orcid":"https://orcid.org/0000-0002-5243-7189"},"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":"Ran Tao","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China","Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Key Laboratory of Fractional Signals and Systems, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101769560"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":22.097,"has_fulltext":false,"cited_by_count":127,"citation_normalized_percentile":{"value":0.99642917,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"12"},"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":0.9986000061035156,"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":0.9986000061035156,"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":0.9955000281333923,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9904999732971191,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.821395993232727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7373960614204407},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6486871838569641},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6001652479171753},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5194132328033447},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47030824422836304},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44160833954811096},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43475914001464844},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40327903628349304},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3727370500564575},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1327252984046936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09135839343070984}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.821395993232727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7373960614204407},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6486871838569641},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6001652479171753},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5194132328033447},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47030824422836304},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44160833954811096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43475914001464844},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40327903628349304},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3727370500564575},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1327252984046936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09135839343070984},{"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.2022.3233885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233885","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":"Quality Education","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2645103404","display_name":null,"funder_award_id":"2021YFB3900502","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4883068204","display_name":null,"funder_award_id":"62001023","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1965309615","https://openalex.org/W2125865219","https://openalex.org/W2312493675","https://openalex.org/W2794905319","https://openalex.org/W2890133123","https://openalex.org/W2962784628","https://openalex.org/W2964288524","https://openalex.org/W2968124245","https://openalex.org/W2968584961","https://openalex.org/W2974291863","https://openalex.org/W2991286101","https://openalex.org/W2991488782","https://openalex.org/W2998712190","https://openalex.org/W3004205097","https://openalex.org/W3012111773","https://openalex.org/W3021632667","https://openalex.org/W3035667144","https://openalex.org/W3098351727","https://openalex.org/W3119997721","https://openalex.org/W3120356488","https://openalex.org/W3124219615","https://openalex.org/W3133289359","https://openalex.org/W3175215201","https://openalex.org/W3175956495","https://openalex.org/W3177224328","https://openalex.org/W3189951784","https://openalex.org/W3194015448","https://openalex.org/W3201461236","https://openalex.org/W3205865791","https://openalex.org/W4214480085","https://openalex.org/W4220716465","https://openalex.org/W4225307291","https://openalex.org/W4229042118","https://openalex.org/W4280563105","https://openalex.org/W4282934494","https://openalex.org/W4283760989","https://openalex.org/W4285106080","https://openalex.org/W4285127355","https://openalex.org/W4285154049","https://openalex.org/W4311415873","https://openalex.org/W4321484009","https://openalex.org/W4385245566","https://openalex.org/W6767279747","https://openalex.org/W6776700526","https://openalex.org/W6790663936","https://openalex.org/W6791353385","https://openalex.org/W6811072154","https://openalex.org/W6811102192","https://openalex.org/W6843355400"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2990774877","https://openalex.org/W3093339210"],"abstract_inverted_index":{"Text":[0],"information":[1],"including":[2,51,120],"extensive":[3],"prior":[4,95],"knowledge":[5,65],"about":[6],"land":[7],"cover":[8],"classes":[9],"has":[10],"been":[11],"ignored":[12],"in":[13,29,45,135,170],"hyperspectral":[14],"image":[15,122],"(HSI)":[16],"classification":[17],"tasks.":[18],"It":[19],"is":[20,86,127,164],"necessary":[21],"to":[22,66,88,112,129,144],"explore":[23],"the":[24,35,68,76,103,110,113,121,179,182,188,197],"effectiveness":[25],"of":[26,48,71,148,181],"linguistic":[27,63,133,149,152],"mode":[28],"assisting":[30],"HSI":[31],"classification.":[32],"In":[33],"addition,":[34],"large-scale":[36],"pretraining":[37],"image\u2013text":[38],"foundation":[39],"models":[40],"have":[41,59],"demonstrated":[42],"great":[43],"performance":[44,70],"a":[46,80],"variety":[47],"downstream":[49],"applications,":[50],"zero-shot":[52],"transfer.":[53],"However,":[54],"most":[55],"domain":[56,82,105,115],"generalization":[57,69,83],"methods":[58],"never":[60],"addressed":[61],"mining":[62],"modal":[64],"improve":[67],"model.":[72],"To":[73],"compensate":[74],"for":[75],"inadequacies":[77],"listed":[78],"above,":[79],"language-aware":[81],"network":[84],"(LDGnet)":[85],"proposed":[87,98,183],"learn":[89],"cross-domain-invariant":[90],"representation":[91],"from":[92,196],"cross-domain":[93,157],"shared":[94,158],"knowledge.":[96],"The":[97,117,191],"method":[99,184],"only":[100],"trains":[101],"on":[102,175],"source":[104],"(SD)":[106],"and":[107,124,132,138,161],"then":[108],"transfers":[109],"model":[111],"target":[114],"(TD).":[116],"dual-stream":[118],"architecture":[119],"encoder":[123,126],"text":[125,140],"used":[128,155],"extract":[130,145],"visual":[131],"features,":[134],"which":[136],"coarse-grained":[137],"fine-grained":[139],"representations":[141],"are":[142,154],"designed":[143],"two":[146],"levels":[147],"features.":[150],"Furthermore,":[151],"features":[153],"as":[156],"semantic":[159,171],"space,":[160],"visual\u2013linguistic":[162],"alignment":[163],"completed":[165],"by":[166],"supervised":[167],"contrastive":[168],"learning":[169],"space.":[172],"Extensive":[173],"experiments":[174],"three":[176],"datasets":[177],"demonstrate":[178],"superiority":[180],"when":[185],"compared":[186],"with":[187],"state-of-the-art":[189],"techniques.":[190],"codes":[192],"will":[193],"be":[194],"available":[195],"website:":[198],"<uri":[199],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[200],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/YuxiangZhang-BIT/IEEE_TGRS_LDGnet</uri>":[201],".":[202]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":61},{"year":2023,"cited_by_count":24}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}