{"id":"https://openalex.org/W4312975848","doi":"https://doi.org/10.1109/tgrs.2022.3225947","title":"Multiview Calibrated Prototype Learning for Few-Shot Hyperspectral Image Classification","display_name":"Multiview Calibrated Prototype Learning for Few-Shot Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312975848","doi":"https://doi.org/10.1109/tgrs.2022.3225947"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3225947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3225947","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/A5100624941","display_name":"Chunyan Yu","orcid":"https://orcid.org/0000-0002-9260-6629"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyan Yu","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-9260-6629","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063579799","display_name":"Baoyu Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoyu Gong","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101405735","display_name":"Meiping Song","orcid":"https://orcid.org/0000-0002-4489-5470"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiping Song","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0002-4489-5470","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031035100","display_name":"Enyu Zhao","orcid":"https://orcid.org/0000-0001-7165-1861"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enyu Zhao","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-7165-1861","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073412670","display_name":"Chein\u2010I Chang","orcid":"https://orcid.org/0000-0002-5450-4891"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]},{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Chein-I Chang","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","Department of Computer Science and Electrical Engineering, Remote Sensing Signal and Image Processing Laboratory, University of Maryland at Baltimore County, Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-5450-4891","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]},{"raw_affiliation_string":"Department of Computer Science and Electrical Engineering, Remote Sensing Signal and Image Processing Laboratory, University of Maryland at Baltimore County, Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0603,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.94700461,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9772999882698059,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9722999930381775,"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/computer-science","display_name":"Computer science","score":0.7593420147895813},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6928143501281738},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6803385615348816},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6071769595146179},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5373436808586121},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5211310982704163},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5012397766113281},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4973621666431427},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.482467919588089},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.460527241230011},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4179297387599945},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33830124139785767},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3211857080459595},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29621389508247375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7593420147895813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6928143501281738},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6803385615348816},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6071769595146179},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5373436808586121},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5211310982704163},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5012397766113281},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4973621666431427},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.482467919588089},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.460527241230011},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4179297387599945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33830124139785767},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3211857080459595},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29621389508247375},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3225947","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3225947","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5299999713897705},{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G5800071179","display_name":"\u57fa\u4e8e\u6d4b\u5ea6\u4fdd\u6301\u548c\u4efb\u52a1\u9a71\u52a8\u7684\u975e\u76d1\u7763\u6ce2\u6bb5\u9009\u62e9\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971082","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7167985160","display_name":null,"funder_award_id":"42271355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8706429153","display_name":null,"funder_award_id":"3132017124","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1971695414","https://openalex.org/W1981166859","https://openalex.org/W2004104348","https://openalex.org/W2084891923","https://openalex.org/W2097238823","https://openalex.org/W2548445115","https://openalex.org/W2548476632","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2753160622","https://openalex.org/W2764276316","https://openalex.org/W2822065499","https://openalex.org/W2888119354","https://openalex.org/W2898204262","https://openalex.org/W2943605315","https://openalex.org/W2944512710","https://openalex.org/W2946747211","https://openalex.org/W2947471972","https://openalex.org/W2962799101","https://openalex.org/W2963341924","https://openalex.org/W2989871747","https://openalex.org/W3011495011","https://openalex.org/W3034251792","https://openalex.org/W3037613841","https://openalex.org/W3043183554","https://openalex.org/W3048029844","https://openalex.org/W3064134516","https://openalex.org/W3083068801","https://openalex.org/W3089684975","https://openalex.org/W3091247454","https://openalex.org/W3091905774","https://openalex.org/W3114720220","https://openalex.org/W3122520870","https://openalex.org/W3124294118","https://openalex.org/W3131437069","https://openalex.org/W3132524115","https://openalex.org/W3132867842","https://openalex.org/W3133055443","https://openalex.org/W3169569276","https://openalex.org/W3189063576","https://openalex.org/W3193205520","https://openalex.org/W3195051845","https://openalex.org/W3195858154","https://openalex.org/W3205269914","https://openalex.org/W3205326557","https://openalex.org/W3206909760","https://openalex.org/W3215588016","https://openalex.org/W4200080982","https://openalex.org/W4225582357","https://openalex.org/W4225630686","https://openalex.org/W4288054357","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6743661861","https://openalex.org/W6783596713","https://openalex.org/W6788840927"],"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/W2070598848","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W4390143830"],"abstract_inverted_index":{"Despite":[0],"continuing":[1],"to":[2,18,49,55,87,106,121,138,158],"progress":[3],"in":[4,21,62,93,163],"hyperspectral":[5,175],"image":[6,176],"classification":[7,14],"(HSIC)":[8],"based":[9],"on":[10],"deep":[11],"learning,":[12],"the":[13,22,31,43,50,60,89,94,98,103,108,115,118,123,126,129,140,143,148,160,164,179,182],"accuracy":[15],"is":[16,102,136],"limited":[17],"furtherly":[19],"improve":[20,88,122],"absence":[23],"of":[24,80,91,117,125,142,151,173,181],"labeled":[25],"samples.":[26],"To":[27],"address":[28],"this":[29,66],"issue,":[30],"metric-based":[32],"prototypical":[33,45],"networks":[34,46],"for":[35,59,75,114],"few-shot":[36,76],"learning":[37,132],"have":[38],"enjoyed":[39],"widespread":[40],"popularity.":[41],"However,":[42],"conventional":[44],"are":[47],"vulnerable":[48],"selected":[51],"examples":[52],"and":[53,171],"fail":[54],"accomplish":[56],"representative":[57],"predictions":[58],"prototypes":[61,92],"complicated":[63],"situations.":[64],"In":[65],"paper,":[67],"we":[68,146],"propose":[69],"a":[70],"multi-view":[71],"calibrated":[72,99,130],"prototype-learning":[73],"framework":[74],"HSIC,":[77],"which":[78],"consists":[79],"three":[81,174],"rectified":[82],"strategies":[83],"from":[84],"different":[85],"views":[86],"robustness":[90],"embedding":[95],"space.":[96],"Specifically,":[97],"aggregation":[100,113],"network":[101],"first":[104],"presented":[105],"calibrate":[107,147],"representations":[109],"with":[110,133,186],"local":[111,161],"patches":[112],"enhancement":[116],"prototypes.":[119,144],"Moreover,":[120],"compactness":[124],"intraclass":[127],"expression,":[128],"metric":[131],"regularization":[134],"terms":[135],"designed":[137],"strengthen":[139],"discrimination":[141],"Furthermore,":[145],"feature":[149],"distribution":[150],"supervised":[152],"samples":[153],"by":[154],"transferring":[155],"statistical":[156],"knowledge":[157],"eliminate":[159],"bias":[162],"test":[165],"phase.":[166],"The":[167],"extensive":[168],"experimental":[169],"results":[170],"analysis":[172],"datasets":[177],"demonstrate":[178],"superiority":[180],"proposed":[183],"architecture":[184],"compared":[185],"other":[187],"advanced":[188],"methods.":[189]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":11}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
