{"id":"https://openalex.org/W4404101631","doi":"https://doi.org/10.1109/tgrs.2024.3492499","title":"Shared-Private Decoupling-Based Multilevel Feature Alignment Semisupervised Learning for HSI and LiDAR Classification","display_name":"Shared-Private Decoupling-Based Multilevel Feature Alignment Semisupervised Learning for HSI and LiDAR Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4404101631","doi":"https://doi.org/10.1109/tgrs.2024.3492499"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3492499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3492499","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/A5044736869","display_name":"Jiahui Qu","orcid":"https://orcid.org/0000-0002-3925-2884"},"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":"Jiahui Qu","raw_affiliation_strings":["State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108924985","display_name":"Lijian Zhang","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":"Lijian Zhang","raw_affiliation_strings":["State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045803591","display_name":"Wenqian Dong","orcid":"https://orcid.org/0000-0002-0692-9676"},"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":"Wenqian Dong","raw_affiliation_strings":["State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013670682","display_name":"Nan Li","orcid":"https://orcid.org/0009-0005-1952-2209"},"institutions":[{"id":"https://openalex.org/I4210115456","display_name":"Chuzhou University","ror":"https://ror.org/037663q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115456"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Li","raw_affiliation_strings":["Anhui Province Key Laboratory of Physical Geographic Environment, Anhui Engineering Research Center of Remote Sensing and Geoinformatics, Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Physical Geographic Environment, Anhui Engineering Research Center of Remote Sensing and Geoinformatics, Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou, China","institution_ids":["https://openalex.org/I4210115456"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067798266","display_name":"Yunsong Li","orcid":"https://orcid.org/0000-0002-0640-4060"},"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":"Yunsong Li","raw_affiliation_strings":["State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Network, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5044736869"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":3.415,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.93463994,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"62","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":0.9674999713897705,"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":0.9674999713897705,"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/lidar","display_name":"Lidar","score":0.792558491230011},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.649520218372345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5598611831665039},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5180209279060364},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.5170324444770813},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5077613592147827},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46367689967155457},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4513111710548401},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15850108861923218},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09439346194267273}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.792558491230011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.649520218372345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5598611831665039},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5180209279060364},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.5170324444770813},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5077613592147827},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46367689967155457},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4513111710548401},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15850108861923218},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09439346194267273},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3492499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3492499","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":[],"awards":[{"id":"https://openalex.org/G1249714260","display_name":null,"funder_award_id":"2023T160502","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G1907377792","display_name":null,"funder_award_id":"2021M702548","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3220876813","display_name":null,"funder_award_id":"2021M702546","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5306284554","display_name":null,"funder_award_id":"62471359","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5516072448","display_name":null,"funder_award_id":"62201423","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8108428442","display_name":null,"funder_award_id":"2022T150508","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G8282386850","display_name":null,"funder_award_id":"62101414","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W2067874135","https://openalex.org/W2606929568","https://openalex.org/W2623518586","https://openalex.org/W2765739551","https://openalex.org/W3081753142","https://openalex.org/W3084798277","https://openalex.org/W3094484482","https://openalex.org/W3133902755","https://openalex.org/W3140885850","https://openalex.org/W3174894125","https://openalex.org/W3208935369","https://openalex.org/W4223616928","https://openalex.org/W4225931144","https://openalex.org/W4312339456","https://openalex.org/W4312465065","https://openalex.org/W4312592451","https://openalex.org/W4312772581","https://openalex.org/W4312865898","https://openalex.org/W4312954132","https://openalex.org/W4313166641","https://openalex.org/W4315606133","https://openalex.org/W4315750685","https://openalex.org/W4361982595","https://openalex.org/W4362690177","https://openalex.org/W4365130851","https://openalex.org/W4366503951","https://openalex.org/W4380763457","https://openalex.org/W4385289414","https://openalex.org/W4387250698","https://openalex.org/W4387789827","https://openalex.org/W4388505065","https://openalex.org/W4390494483","https://openalex.org/W4391467954","https://openalex.org/W4391528302","https://openalex.org/W4391594050","https://openalex.org/W4392566508","https://openalex.org/W4394773589","https://openalex.org/W4399110322","https://openalex.org/W4399206013","https://openalex.org/W4399310774","https://openalex.org/W4399343207","https://openalex.org/W4399527005","https://openalex.org/W4399666114","https://openalex.org/W4399849901","https://openalex.org/W4400062116","https://openalex.org/W4401879860","https://openalex.org/W4402041492","https://openalex.org/W6685261749","https://openalex.org/W6725448924","https://openalex.org/W6802864417","https://openalex.org/W6839041728"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W2351984678","https://openalex.org/W2140032575","https://openalex.org/W2011860471","https://openalex.org/W2012196540","https://openalex.org/W3011451421"],"abstract_inverted_index":{"The":[0,131,219],"joint":[1],"classification":[2,22,78],"methods":[3],"of":[4,63,72,122,215],"hyperspectral":[5],"image":[6],"(HSI)":[7],"and":[8,11,32,56,74,79,102,110,124,146,193],"light":[9],"detection":[10],"ranging":[12],"(LiDAR)":[13],"data":[14,76,96,104],"based":[15,84],"on":[16,85,208],"deep":[17],"learning":[18,52],"have":[19],"demonstrated":[20],"exceptional":[21],"performance":[23],"with":[24,176],"sufficient":[25],"labeled":[26,36,73,95],"samples.":[27],"However,":[28],"it":[29],"is":[30,138,221],"expensive":[31],"time-consuming":[33],"to":[34,67,88,118,140,189],"acquire":[35,119],"data.":[37],"To":[38],"address":[39],"this":[40],"limitation,":[41],"we":[42,93,162],"propose":[43,111],"a":[44,112,164],"shared-private":[45,113],"decoupling-based":[46],"multilevel":[47,132],"feature":[48,114,134],"alignment":[49,135],"semisupervised":[50],"(SASS)":[51],"method":[53],"for":[54,77,172],"HSI":[55],"LiDAR":[57],"classification,":[58],"which":[59,179],"introduces":[60],"the":[61,69,90,98,106,151,181,198,213,216],"idea":[62],"domain":[64,100,108,128],"adaptation":[65],"(DA)":[66],"capture":[68],"shared":[70,120,133,158],"features":[71,87],"unlabeled":[75,103],"circularly":[80],"selects":[81],"reliable":[82,177],"pseudolabels":[83,196],"these":[86,157],"retrain":[89],"model.":[91],"Specifically,":[92],"treat":[94],"as":[97,105],"source":[99],"(SD)":[101],"target":[107],"(TD)":[109],"decoupling":[115],"(SPFD)":[116],"module":[117],"representations":[121],"SD":[123],"TD":[125],"by":[126,149],"separating":[127],"private":[129],"features.":[130,159],"(MSFA)":[136],"strategy":[137,171,188],"designed":[139],"synthetically":[141],"consider":[142],"both":[143],"spatial":[144],"details":[145],"semantic":[147],"information":[148],"minimizing":[150],"maximum":[152],"mean":[153],"discrepancy":[154],"(MMD)":[155],"between":[156],"In":[160],"addition,":[161],"design":[163],"graph":[165,182],"transformer-based":[166],"class-balanced":[167],"pseudolabel":[168],"generation":[169],"(GBPG)":[170],"iterative":[173],"model":[174],"training":[175],"pseudolabels,":[178],"exploits":[180],"transformer":[183],"network-based":[184],"sample":[185,202],"acquisition":[186],"(GTSA)":[187],"select":[190],"valuable":[191],"samples":[192],"generate":[194],"corresponding":[195],"using":[197],"adaptive":[199],"class-specific":[200],"threshold-based":[201],"annotation":[203],"(ATSA)":[204],"strategy.":[205],"Experimental":[206],"results":[207],"three":[209],"public":[210],"datasets":[211],"validate":[212],"effectiveness":[214],"proposed":[217],"method.":[218],"code":[220],"available":[222],"at":[223],"<uri":[224],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/Jiahuiqu/SASS</uri>.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
