{"id":"https://openalex.org/W4288054357","doi":"https://doi.org/10.1109/tip.2022.3192712","title":"Few-Shot Learning With Class-Covariance Metric for Hyperspectral Image Classification","display_name":"Few-Shot Learning With Class-Covariance Metric for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4288054357","doi":"https://doi.org/10.1109/tip.2022.3192712","pmid":"https://pubmed.ncbi.nlm.nih.gov/35881603"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3192712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3192712","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5006601447","display_name":"Bobo Xi","orcid":"https://orcid.org/0000-0002-0309-1556"},"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":"Bobo Xi","raw_affiliation_strings":["State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","an, China"],"raw_orcid":"https://orcid.org/0000-0002-0309-1556","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100734649","display_name":"Jiaojiao Li","orcid":"https://orcid.org/0000-0002-0470-9469"},"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":"Jiaojiao Li","raw_affiliation_strings":["State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","an, China"],"raw_orcid":"https://orcid.org/0000-0002-0470-9469","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067798266","display_name":"Yunsong Li","orcid":"https://orcid.org/0000-0002-0234-6270"},"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 Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","an, China"],"raw_orcid":"https://orcid.org/0000-0002-0234-6270","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057594828","display_name":"Rui Song","orcid":"https://orcid.org/0000-0002-2790-1752"},"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":"Rui Song","raw_affiliation_strings":["State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","an, China"],"raw_orcid":"https://orcid.org/0000-0002-2790-1752","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, School of Telecommunications Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"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/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","Aerospace Information Research Institute, Key Laboratory of Computational Optical Imaging Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3212-9584","affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Key Laboratory of Computational Optical Imaging Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"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/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN","FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["GIPSA-Laboratory, CNRS, Grenoble INP, Université Grenoble Alpes, Grenoble, France","Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4817-2875","affiliations":[{"raw_affiliation_string":"GIPSA-Laboratory, CNRS, Grenoble INP, Université Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.9969,"has_fulltext":false,"cited_by_count":178,"citation_normalized_percentile":{"value":0.99511241,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"31","issue":null,"first_page":"5079","last_page":"5092"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9757999777793884,"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/T12676","display_name":"Machine Learning and ELM","score":0.9708999991416931,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7782741189002991},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.705363392829895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6957445740699768},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6505305767059326},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5471044182777405},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5231655836105347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5106526017189026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45992550253868103},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4404904246330261},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.425920695066452},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35095494985580444},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33869415521621704},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18532723188400269}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7782741189002991},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.705363392829895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6957445740699768},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6505305767059326},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5471044182777405},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5231655836105347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5106526017189026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45992550253868103},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4404904246330261},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.425920695066452},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35095494985580444},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33869415521621704},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18532723188400269},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2022.3192712","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3192712","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:35881603","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35881603","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:HAL:hal-03932377v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03932377","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Image Processing, 2022, 31, pp.5079-5092. ⟨10.1109/TIP.2022.3192712⟩","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G1041279674","display_name":"MIAI @ Grenoble Alpes","funder_award_id":"ANR-19-P3IA-0003","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G1192011550","display_name":null,"funder_award_id":"2018T111019","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G1595715893","display_name":null,"funder_award_id":"B08038","funder_id":"https://openalex.org/F4320327912","funder_display_name":"Higher Education Discipline Innovation Project"},{"id":"https://openalex.org/G4801475360","display_name":"\u57fa\u4e8e\u7a00\u758f\u4f4e\u79e9\u8868\u793a\u4e0e\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u7684\u9ad8\u5149\u8c31\u56fe\u50cf\u5149\u8c31\u53d8\u5316\u5904\u7406\u7814\u7a76","funder_award_id":"61671383","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G545722288","display_name":null,"funder_award_id":"XWYCXY-012021002","funder_id":"https://openalex.org/F4320323230","funder_display_name":"Xidian University"},{"id":"https://openalex.org/G5657849150","display_name":null,"funder_award_id":"91538101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6255080559","display_name":null,"funder_award_id":"61901343","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G822648524","display_name":null,"funder_award_id":"SKLGIE2020-M-3-1","funder_id":"https://openalex.org/F4320326985","funder_display_name":"State Key Laboratory of Geo-Information Engineering"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"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"},{"id":"https://openalex.org/F4320323230","display_name":"Xidian University","ror":"https://ror.org/05s92vm98"},{"id":"https://openalex.org/F4320326985","display_name":"State Key Laboratory of Geo-Information Engineering","ror":null},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1966580635","https://openalex.org/W2007621462","https://openalex.org/W2053186076","https://openalex.org/W2114819256","https://openalex.org/W2162698522","https://openalex.org/W2187089797","https://openalex.org/W2500751094","https://openalex.org/W2519956323","https://openalex.org/W2572303978","https://openalex.org/W2612690371","https://openalex.org/W2614256707","https://openalex.org/W2752782242","https://openalex.org/W2754507318","https://openalex.org/W2764276316","https://openalex.org/W2767805377","https://openalex.org/W2768975974","https://openalex.org/W2782517596","https://openalex.org/W2799954862","https://openalex.org/W2809113079","https://openalex.org/W2822065499","https://openalex.org/W2898204262","https://openalex.org/W2914331134","https://openalex.org/W2942454403","https://openalex.org/W2950325582","https://openalex.org/W2962770389","https://openalex.org/W2977002487","https://openalex.org/W2984353870","https://openalex.org/W2988396473","https://openalex.org/W2991286101","https://openalex.org/W2991616716","https://openalex.org/W2994639710","https://openalex.org/W2995099525","https://openalex.org/W3006984222","https://openalex.org/W3023736619","https://openalex.org/W3031696400","https://openalex.org/W3034552520","https://openalex.org/W3034587791","https://openalex.org/W3034942609","https://openalex.org/W3037613841","https://openalex.org/W3043181422","https://openalex.org/W3043183554","https://openalex.org/W3046027728","https://openalex.org/W3064134516","https://openalex.org/W3089256253","https://openalex.org/W3092053846","https://openalex.org/W3096751897","https://openalex.org/W3098388691","https://openalex.org/W3103753223","https://openalex.org/W3105100264","https://openalex.org/W3105298104","https://openalex.org/W3119622049","https://openalex.org/W3122774149","https://openalex.org/W3127230150","https://openalex.org/W3132867842","https://openalex.org/W3133271982","https://openalex.org/W3134743586","https://openalex.org/W3138725786","https://openalex.org/W3154934604","https://openalex.org/W3181932393","https://openalex.org/W3189063576","https://openalex.org/W3204445362","https://openalex.org/W3207818847","https://openalex.org/W4205124618","https://openalex.org/W4206104510","https://openalex.org/W4220841454","https://openalex.org/W4220894989","https://openalex.org/W4225688999","https://openalex.org/W6717697761","https://openalex.org/W6735236233"],"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/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3093143829"],"abstract_inverted_index":{"Recently,":[0],"embedding":[1,202],"and":[2,15,63,66,82,130,144,195],"metric-based":[3],"few-shot":[4,223],"learning":[5],"(FSL)":[6],"has":[7],"been":[8],"introduced":[9],"into":[10],"hyperspectral":[11],"image":[12],"classification":[13],"(HSIC)":[14],"achieved":[16],"impressive":[17],"progress.":[18],"To":[19],"further":[20],"enhance":[21],"the":[22,45,61,73,80,84,91,102,106,115,138,142,160,170,174,180,186,189,193,214,219],"performance":[23],"with":[24,39,147,222],"few":[25],"labeled":[26],"samples,":[27],"we":[28,152],"in":[29,141,159],"this":[30],"paper":[31],"propose":[32],"a":[33,40,67,121,154,200],"novel":[34,64,74,196],"FSL":[35],"framework":[36],"for":[37,51],"HSIC":[38],"class-covariance":[41,104],"metric":[42],"(CMFSL).":[43],"Overall,":[44],"CMFSL":[46,107,216],"learns":[47],"global":[48],"class":[49,85],"representations":[50],"each":[52],"training":[53,58],"episode":[54],"by":[55],"interactively":[56],"using":[57,90],"samples":[59],"from":[60,101],"base":[62,194],"classes,":[65],"synthesis":[68],"strategy":[69],"is":[70,133],"employed":[71],"on":[72,207],"classes":[75],"to":[76,135,172,198],"avoid":[77],"overfitting.":[78],"During":[79],"meta-training":[81],"meta-testing,":[83],"labels":[86],"are":[87],"determined":[88],"directly":[89],"Mahalanobis":[92],"distance":[93],"measurement":[94],"rather":[95],"than":[96,114],"an":[97],"extra":[98],"classifier.":[99],"Benefiting":[100],"task-adapted":[103],"estimations,":[105],"can":[108,217],"construct":[109],"more":[110],"flexible":[111],"decision":[112],"boundaries":[113],"commonly":[116],"used":[117],"Euclidean":[118],"metric.":[119],"Additionally,":[120],"lightweight":[122],"cross-scale":[123],"convolutional":[124],"network":[125,171],"(LXConvNet)":[126],"consisting":[127],"of":[128,163,188],"3D":[129],"2D":[131],"convolutions":[132],"designed":[134],"thoroughly":[136],"exploit":[137],"spectral-spatial":[139],"information":[140],"high-frequency":[143],"low-frequency":[145],"scales":[146],"low":[148],"computational":[149],"complexity.":[150],"Furthermore,":[151],"devise":[153],"spectral-prior-based":[155],"refinement":[156],"module":[157],"(SPRM)":[158],"initial":[161],"stage":[162],"feature":[164],"extraction,":[165],"which":[166],"cannot":[167],"only":[168],"force":[169],"emphasize":[173],"most":[175],"informative":[176],"bands":[177],"while":[178],"suppressing":[179],"useless":[181],"ones,":[182],"but":[183],"also":[184],"alleviate":[185],"effects":[187],"domain":[190],"shift":[191],"between":[192],"categories":[197],"learn":[199],"collaborative":[201],"mapping.":[203],"Extensive":[204],"experiment":[205],"results":[206],"four":[208],"benchmark":[209],"data":[210],"sets":[211],"demonstrate":[212],"that":[213],"proposed":[215],"outperform":[218],"state-of-the-art":[220],"methods":[221],"annotated":[224],"samples.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":73},{"year":2024,"cited_by_count":57},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}