{"id":"https://openalex.org/W4382721750","doi":"https://doi.org/10.1109/jstars.2023.3290678","title":"Dual-Branch Spectral\u2013Spatial Adversarial Representation Learning for Hyperspectral Image Classification With Few Labeled Samples","display_name":"Dual-Branch Spectral\u2013Spatial Adversarial Representation Learning for Hyperspectral Image Classification With Few Labeled Samples","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4382721750","doi":"https://doi.org/10.1109/jstars.2023.3290678"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2023.3290678","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3290678","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10168240.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10168240.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044784805","display_name":"Caihao Sun","orcid":"https://orcid.org/0000-0002-8164-489X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Caihao Sun","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100445822","display_name":"Xiaohua Zhang","orcid":"https://orcid.org/0009-0007-6783-4586"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062573283","display_name":"Hongyun Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyun Meng","raw_affiliation_strings":["School of Mathematics and Statistics, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100681906","display_name":"Xianghai Cao","orcid":"https://orcid.org/0000-0003-0997-4664"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghai Cao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393296","display_name":"Jinhua Zhang","orcid":"https://orcid.org/0009-0005-2347-8677"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhua Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050630882","display_name":"Licheng Jiao","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Licheng Jiao","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5044784805"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.9442,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78027128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9936000108718872,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7810491323471069},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7549951076507568},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7442700862884521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.673076868057251},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6488015055656433},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5232518911361694},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4985508918762207},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4898821711540222},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4504951238632202},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3271758556365967},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.295986533164978},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29037052392959595}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7810491323471069},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7549951076507568},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7442700862884521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673076868057251},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6488015055656433},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5232518911361694},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4985508918762207},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4898821711540222},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4504951238632202},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3271758556365967},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.295986533164978},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29037052392959595},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2023.3290678","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3290678","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10168240.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2eb02c9a7e4540e09dcc4b240cae91a6","is_oa":true,"landing_page_url":"https://doaj.org/article/2eb02c9a7e4540e09dcc4b240cae91a6","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 1-15 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2023.3290678","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2023.3290678","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/4609444/10168240.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7886416700","display_name":null,"funder_award_id":"61877066","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4382721750.pdf","grobid_xml":"https://content.openalex.org/works/W4382721750.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1939429412","https://openalex.org/W1948819007","https://openalex.org/W1978074368","https://openalex.org/W2017014096","https://openalex.org/W2029316659","https://openalex.org/W2046817177","https://openalex.org/W2066724243","https://openalex.org/W2069231830","https://openalex.org/W2090424610","https://openalex.org/W2121338139","https://openalex.org/W2125389028","https://openalex.org/W2136251662","https://openalex.org/W2136922672","https://openalex.org/W2154240401","https://openalex.org/W2275923927","https://openalex.org/W2546942002","https://openalex.org/W2572303978","https://openalex.org/W2618017917","https://openalex.org/W2739748921","https://openalex.org/W2761781479","https://openalex.org/W2765452533","https://openalex.org/W2791006446","https://openalex.org/W2900116731","https://openalex.org/W2900614378","https://openalex.org/W2914331134","https://openalex.org/W2942454403","https://openalex.org/W2950776302","https://openalex.org/W2951171145","https://openalex.org/W2962793481","https://openalex.org/W2963684088","https://openalex.org/W2987869696","https://openalex.org/W3022592629","https://openalex.org/W3031696400","https://openalex.org/W3049655825","https://openalex.org/W3139745482","https://openalex.org/W3187061456","https://openalex.org/W4206307542","https://openalex.org/W4210794570","https://openalex.org/W4225685398","https://openalex.org/W4225984886","https://openalex.org/W4285208279","https://openalex.org/W4285262969","https://openalex.org/W4285264965","https://openalex.org/W4287888485","https://openalex.org/W4289792768","https://openalex.org/W4290044412","https://openalex.org/W4292348010","https://openalex.org/W4293068858","https://openalex.org/W4293370522","https://openalex.org/W4303980712","https://openalex.org/W4312811001","https://openalex.org/W4317951215","https://openalex.org/W6729482032","https://openalex.org/W6738248287","https://openalex.org/W6741832134","https://openalex.org/W6792306229","https://openalex.org/W6807144946","https://openalex.org/W6849119191"],"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/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W4309346246","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,158],"learning":[2,71,159],"methods,":[3],"particularly":[4],"the":[5,45,130,157],"convolutional":[6],"neural":[7],"networks,":[8],"have":[9],"been":[10],"extensively":[11],"employed":[12],"for":[13,74,141,183],"extracting":[14],"spectral-spatial":[15],"features":[16,40],"in":[17],"hyperspectral":[18],"image":[19,31],"(HSI)":[20],"classification":[21,127],"tasks,":[22],"yielding":[23],"promising":[24],"results.":[25],"Conventional":[26],"methods":[27,173],"often":[28],"use":[29],"small":[30],"patches":[32,53,135],"as":[33],"input":[34],"and":[35,38,85,108,114,125,136,144,149,179],"combine":[36],"spectral":[37,88,107,124],"spatial":[39,91,109,126],"with":[41],"fixed":[42],"strategies.":[43],"However,":[44],"equal":[46],"treatment":[47],"of":[48,96,133],"all":[49],"pixels":[50,84],"within":[51],"heterogeneous":[52,134],"can":[54],"negatively":[55],"impact":[56],"feature":[57,139],"extraction":[58],"performance.":[59],"In":[60],"this":[61],"article,":[62],"we":[63],"propose":[64],"a":[65,87,100,117],"semi-supervised":[66],"dual-branch":[67,101],"spectralspatial":[68],"adversarial":[69,146],"representation":[70,147],"(SSARL)":[72],"method":[73],"HSI":[75],"classification.":[76],"SSARL":[77,170],"adaptively":[78,122],"assigns":[79],"attention":[80],"weights":[81],"to":[82,90,104,153],"different":[83],"adds":[86],"constraint":[89],"features.":[92],"Our":[93],"approach":[94],"consists":[95],"three":[97],"main":[98],"components:":[99],"framework":[102],"designed":[103],"independently":[105],"extract":[106],"information":[110],"from":[111],"pixel":[112],"samples":[113,178],"patch":[115],"samples,":[116],"class":[118],"consistency":[119],"loss":[120],"that":[121,169],"combines":[123],"results,":[128],"mitigating":[129],"adverse":[131],"effects":[132],"enabling":[137],"appropriate":[138],"selection":[140],"various":[142],"situations,":[143],"an":[145],"module":[148],"conditional":[150],"entropy":[151],"addition":[152],"both":[154],"branches,":[155],"reducing":[156],"model's":[160],"reliance":[161],"on":[162,174],"labeled":[163,177],"sample":[164],"size.":[165],"Experimental":[166],"results":[167],"demonstrate":[168],"outperforms":[171],"competitive":[172],"small-sized":[175],"(0.3%-5%)":[176],"exhibits":[180],"superior":[181],"performance":[182],"boundary":[184],"test":[185],"pixels.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}