{"id":"https://openalex.org/W4415481132","doi":"https://doi.org/10.1109/tgrs.2025.3624835","title":"Is Meta-Learning Effective for Few-Shot Hyperspectral Image Classification?","display_name":"Is Meta-Learning Effective for Few-Shot Hyperspectral Image Classification?","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415481132","doi":"https://doi.org/10.1109/tgrs.2025.3624835"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3624835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3624835","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/A5080198746","display_name":"Li Shen","orcid":"https://orcid.org/0000-0001-6520-1418"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Shen","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102958793","display_name":"Yangzhu Wang","orcid":"https://orcid.org/0000-0003-1309-589X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangzhu Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaoman Zhang","orcid":"https://orcid.org/0009-0004-0011-7433"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoman Zhang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038659681","display_name":"Huaxin Qiu","orcid":"https://orcid.org/0000-0002-6995-7367"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaxin Qiu","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101596698","display_name":"Zhenyang Zhang","orcid":"https://orcid.org/0009-0000-2821-7736"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenyang Zhang","raw_affiliation_strings":["China Tower Corporation Ltd., Beijing, China","China Tower Corporation Limited, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Tower Corporation Ltd., Beijing, China","institution_ids":[]},{"raw_affiliation_string":"China Tower Corporation Limited, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080056008","display_name":"Chang Nie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang Nie","raw_affiliation_strings":["China Tower Corporation Ltd., Beijing, China","China Tower Corporation Limited, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Tower Corporation Ltd., Beijing, China","institution_ids":[]},{"raw_affiliation_string":"China Tower Corporation Limited, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100318397","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-2152-4172"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5080198746"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42609962,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9301999807357788,"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":0.9301999807357788,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8568999767303467},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6168000102043152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5083000063896179},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45170000195503235},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.38350000977516174},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3684000074863434},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3456999957561493}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8568999767303467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.758400022983551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6764000058174133},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6168000102043152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5083000063896179},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45170000195503235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4334000051021576},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3562000095844269},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3456999957561493},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.3174000084400177},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.26899999380111694}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3624835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3624835","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/G5006583825","display_name":null,"funder_award_id":"GPDI-ZB-2024-01141","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5131996793","display_name":null,"funder_award_id":"62103414","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":42,"referenced_works":["https://openalex.org/W1995734767","https://openalex.org/W2023791222","https://openalex.org/W2506684654","https://openalex.org/W2582369608","https://openalex.org/W2767805377","https://openalex.org/W2782517596","https://openalex.org/W2796684832","https://openalex.org/W2898204262","https://openalex.org/W2931204392","https://openalex.org/W2971262044","https://openalex.org/W2997616671","https://openalex.org/W3121523901","https://openalex.org/W3138516171","https://openalex.org/W3199596098","https://openalex.org/W4210927230","https://openalex.org/W4211244138","https://openalex.org/W4214634256","https://openalex.org/W4283760989","https://openalex.org/W4312899742","https://openalex.org/W4313229425","https://openalex.org/W4313476641","https://openalex.org/W4313525856","https://openalex.org/W4319065888","https://openalex.org/W4320339642","https://openalex.org/W4380318427","https://openalex.org/W4385256752","https://openalex.org/W4385864282","https://openalex.org/W4387848755","https://openalex.org/W4387987050","https://openalex.org/W4392904001","https://openalex.org/W4394002302","https://openalex.org/W4394585843","https://openalex.org/W4397000037","https://openalex.org/W4399169000","https://openalex.org/W4402674148","https://openalex.org/W4402716014","https://openalex.org/W4402912975","https://openalex.org/W4403210136","https://openalex.org/W4403601086","https://openalex.org/W4404566085","https://openalex.org/W4406345449","https://openalex.org/W4406856751"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"there":[1],"has":[2],"been":[3],"a":[4,23,30,81,107,120],"surge":[5],"of":[6,39,63,160,171,181,190],"meta-learning-based":[7,99,137,172],"approaches":[8],"for":[9,84,115],"the":[10,37,40,60,67,93,125,130,158,166,179,186],"few-shot":[11,32],"hyperspectral":[12,49,61],"image":[13,50],"classification":[14,51,169],"(FSHSIC)":[15],"task.":[16],"Meta-learning":[17],"leverages":[18],"prior":[19,41],"knowledge":[20],"to":[21,26,29,45,90,128,178],"teach":[22],"base-learner":[24],"how":[25],"adapt":[27],"quickly":[28],"new":[31,43],"task,":[33,56],"which":[34,57,139],"hinges":[35],"on":[36,196],"consistency":[38],"and":[42,148],"tasks":[44],"guarantee":[46],"validity.":[47],"However,":[48],"(HSIC)":[52],"is":[53,80,86,194],"an":[54,87],"environment-dependent":[55],"means":[58],"that":[59,165],"features":[62],"two":[64],"objects":[65],"in":[66,74,97,153],"same":[68],"category":[69],"can":[70],"be":[71],"essentially":[72],"distinctive":[73],"different":[75],"environments.":[76],"Consequently,":[77],"whether":[78],"meta-learning":[79],"feasible":[82],"solution":[83],"FSHSIC":[85,173],"imperative":[88],"problem":[89],"investigate,":[91],"notwithstanding":[92],"promising":[94],"performance":[95],"shown":[96],"previous":[98],"approaches.":[100],"To":[101],"this":[102,104],"end,":[103],"work":[105],"proposes":[106],"simple":[108],"multilayer":[109],"perceptron":[110],"(MLP)-based":[111],"model":[112,131],"named":[113],"SimHSIC":[114,117,134],"FSHSIC.":[116],"utilizes":[118],"only":[119],"few":[121],"labeled":[122],"samples":[123],"from":[124],"target":[126],"HSI":[127,183],"train":[129],"rapidly.":[132],"Surprisingly,":[133],"outperforms":[135],"existing":[136],"approaches,":[138],"are":[140,175],"built":[141],"upon":[142],"complex":[143],"three-dimensional":[144],"convolutions":[145],"or":[146],"transformers":[147],"need":[149],"heavy":[150],"training":[151],"processes,":[152],"prevailing":[154],"public":[155],"benchmarks.":[156],"On":[157],"basis":[159],"extensive":[161],"experiments,":[162],"we":[163],"conclude":[164],"relatively":[167],"better":[168],"performances":[170],"solutions":[174],"due":[176],"mainly":[177],"patching":[180],"each":[182],"pixel":[184],"with":[185],"large":[187],"surroundings":[188],"instead":[189],"meta-learning.":[191],"The":[192],"code":[193],"released":[195],"https://github.com/OrigamiSL/SimHSIC.":[197]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-23T00:00:00"}