{"id":"https://openalex.org/W2942346439","doi":"https://doi.org/10.1109/lgrs.2019.2909543","title":"Extreme Learning Machine-Based Heterogeneous Domain Adaptation for Classification of Hyperspectral Images","display_name":"Extreme Learning Machine-Based Heterogeneous Domain Adaptation for Classification of Hyperspectral Images","publication_year":2019,"publication_date":"2019-04-27","ids":{"openalex":"https://openalex.org/W2942346439","doi":"https://doi.org/10.1109/lgrs.2019.2909543","mag":"2942346439"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2019.2909543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2909543","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5081045402","display_name":"Li Zhou","orcid":"https://orcid.org/0000-0003-2142-2811"},"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":true,"raw_author_name":"Li Zhou","raw_affiliation_strings":["School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100681694","display_name":"Li Ma","orcid":"https://orcid.org/0000-0003-3873-5080"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"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"]},{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ma","raw_affiliation_strings":["Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences, Xi\u2019an, China","School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China","Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-3873-5080","affiliations":[{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences, Xi'an, China","institution_ids":["https://openalex.org/I4210144662","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081045402"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":2.4564,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.91582311,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"16","issue":"11","first_page":"1781","last_page":"1785"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9965000152587891,"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":0.992900013923645,"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/extreme-learning-machine","display_name":"Extreme learning machine","score":0.8512804508209229},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7611411809921265},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7469593286514282},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6986401677131653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6350405216217041},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6114386320114136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5955566167831421},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4897885322570801},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.48005804419517517},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.475010484457016},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4682522714138031},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4457119107246399},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43133223056793213},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.41431349515914917},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4064418077468872},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27763116359710693},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2539865970611572},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.2053554654121399},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07276439666748047}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.8512804508209229},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7611411809921265},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7469593286514282},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6986401677131653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6350405216217041},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6114386320114136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5955566167831421},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4897885322570801},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.48005804419517517},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.475010484457016},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4682522714138031},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4457119107246399},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43133223056793213},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.41431349515914917},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4064418077468872},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27763116359710693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2539865970611572},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.2053554654121399},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07276439666748047},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2019.2909543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2019.2909543","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G278469076","display_name":null,"funder_award_id":"61771437","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4630198311","display_name":null,"funder_award_id":"91442201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G691914066","display_name":null,"funder_award_id":"61102104","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7223409659","display_name":null,"funder_award_id":"LSIT201702D","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W46086471","https://openalex.org/W1565176903","https://openalex.org/W1834646128","https://openalex.org/W1994348648","https://openalex.org/W2036842392","https://openalex.org/W2054022051","https://openalex.org/W2072187267","https://openalex.org/W2088748973","https://openalex.org/W2090923791","https://openalex.org/W2134603844","https://openalex.org/W2170607218","https://openalex.org/W2240757205","https://openalex.org/W2274622268","https://openalex.org/W2294202617","https://openalex.org/W2395579298","https://openalex.org/W2493435490","https://openalex.org/W2592737629","https://openalex.org/W2741214337","https://openalex.org/W2747311654","https://openalex.org/W2756833625","https://openalex.org/W2792088634","https://openalex.org/W2799954862","https://openalex.org/W2889192935","https://openalex.org/W2890732922","https://openalex.org/W2949280493","https://openalex.org/W3105100264","https://openalex.org/W3106090851","https://openalex.org/W3154664134","https://openalex.org/W4288076010","https://openalex.org/W6601848957","https://openalex.org/W6633602821","https://openalex.org/W6638894083","https://openalex.org/W6679935922"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W3105934373","https://openalex.org/W3034953390","https://openalex.org/W2124697602"],"abstract_inverted_index":{"An":[0],"extreme":[1],"learning":[2],"machine":[3],"(ELM)-based":[4],"heterogeneous":[5],"domain":[6],"adaptation":[7],"(HDA)":[8],"algorithm":[9],"is":[10,27,59,81,98],"proposed":[11,93,121],"for":[12,29,44],"the":[13,20,30,35,49,64,68,74,85,108,117,120],"classification":[14,102],"of":[15,88,103,119],"remote":[16,104,113],"sensing":[17,105,114],"images.":[18],"In":[19],"adaptive":[21],"ELM":[22],"network,":[23],"one":[24],"hidden":[25,40],"layer":[26],"used":[28],"source":[31,65],"data":[32,46,66,71],"to":[33,47,72,83,100],"provide":[34],"random":[36,50],"features,":[37],"whereas":[38],"two":[39],"layers":[41],"are":[42],"set":[43],"target":[45,70,90],"produce":[48],"features":[51],"as":[52,54],"well":[53],"a":[55],"transformation":[56],"matrix.":[57],"DA":[58],"achieved":[60],"by":[61],"constraining":[62],"both":[63],"and":[67,107],"transformed":[69],"share":[73],"same":[75],"output":[76],"weights.":[77],"Moreover,":[78],"manifold":[79],"regularization":[80],"adopted":[82],"preserve":[84],"local":[86],"geometry":[87],"unlabeled":[89],"data.":[91],"The":[92],"ELM-based":[94],"HDA":[95],"(EHDA)":[96],"method":[97],"applied":[99],"cross-domain":[101],"images,":[106],"experimental":[109],"results":[110],"using":[111],"multisensor":[112],"images":[115],"demonstrate":[116],"effectiveness":[118],"approach.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
