{"id":"https://openalex.org/W2146987667","doi":"https://doi.org/10.1109/tgrs.2009.2031812","title":"A Nonparametric Feature Extraction and Its Application to Nearest Neighbor Classification for Hyperspectral Image Data","display_name":"A Nonparametric Feature Extraction and Its Application to Nearest Neighbor Classification for Hyperspectral Image Data","publication_year":2009,"publication_date":"2009-11-03","ids":{"openalex":"https://openalex.org/W2146987667","doi":"https://doi.org/10.1109/tgrs.2009.2031812","mag":"2146987667"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2009.2031812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2009.2031812","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/A5111780992","display_name":"Jinn\u2010Min Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]},{"id":"https://openalex.org/I34574549","display_name":"National Taichung University of Education","ror":"https://ror.org/006tnfe02","country_code":"TW","type":"education","lineage":["https://openalex.org/I34574549"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jinn-Min Yang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan","Department of Mathematics Education, National Taichung University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Department of Mathematics Education, National Taichung University, Taichung, Taiwan","institution_ids":["https://openalex.org/I34574549"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113844352","display_name":"Pao-Ta Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pao-Ta Yu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054302891","display_name":"Bor\u2010Chen Kuo","orcid":"https://orcid.org/0000-0003-1741-2450"},"institutions":[{"id":"https://openalex.org/I34574549","display_name":"National Taichung University of Education","ror":"https://ror.org/006tnfe02","country_code":"TW","type":"education","lineage":["https://openalex.org/I34574549"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bor-Chen Kuo","raw_affiliation_strings":["Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate Institute of Educational Measurement and Statistics, National Taichung University, Taichung, Taiwan","institution_ids":["https://openalex.org/I34574549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.1479,"has_fulltext":false,"cited_by_count":139,"citation_normalized_percentile":{"value":0.98637509,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"48","issue":"3","first_page":"1279","last_page":"1293"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9837999939918518,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.795235276222229},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7532538175582886},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7282443046569824},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.7093959450721741},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6948715448379517},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6805857419967651},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6303147673606873},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4834488332271576},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4473426342010498},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4442570209503174},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42002496123313904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.283507764339447},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21858125925064087},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10871955752372742}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.795235276222229},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7532538175582886},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7282443046569824},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.7093959450721741},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6948715448379517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6805857419967651},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6303147673606873},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4834488332271576},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4473426342010498},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4442570209503174},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42002496123313904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.283507764339447},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21858125925064087},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10871955752372742},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2009.2031812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2009.2031812","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":0.7300000190734863}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W628438000","https://openalex.org/W817971873","https://openalex.org/W1490338671","https://openalex.org/W1522648475","https://openalex.org/W1966285673","https://openalex.org/W1993201782","https://openalex.org/W2002645541","https://openalex.org/W2014949624","https://openalex.org/W2021455849","https://openalex.org/W2022470997","https://openalex.org/W2040171177","https://openalex.org/W2040895929","https://openalex.org/W2070424424","https://openalex.org/W2085535170","https://openalex.org/W2096201283","https://openalex.org/W2096634748","https://openalex.org/W2097900616","https://openalex.org/W2098057602","https://openalex.org/W2109943925","https://openalex.org/W2113076747","https://openalex.org/W2117501368","https://openalex.org/W2118796925","https://openalex.org/W2122780641","https://openalex.org/W2135346934","https://openalex.org/W2135758523","https://openalex.org/W2136809053","https://openalex.org/W2146820706","https://openalex.org/W2148603752","https://openalex.org/W2151194815","https://openalex.org/W2154436408","https://openalex.org/W2154952114","https://openalex.org/W2161943337","https://openalex.org/W2162698522","https://openalex.org/W2164488484","https://openalex.org/W2165533158","https://openalex.org/W2165932235","https://openalex.org/W2167011208","https://openalex.org/W2169567041","https://openalex.org/W2170768877","https://openalex.org/W2406093411","https://openalex.org/W2478493250","https://openalex.org/W3148625633","https://openalex.org/W4244494905","https://openalex.org/W4285719527","https://openalex.org/W4298266977","https://openalex.org/W6623043969","https://openalex.org/W6677540865"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2060875994","https://openalex.org/W2027399350","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W2343470940","https://openalex.org/W3023858869"],"abstract_inverted_index":{"Feature":[0],"extraction":[1,12,49,55],"plays":[2],"an":[3],"essential":[4],"role":[5],"in":[6,59,65],"hyperspectral":[7,118],"image":[8],"classification.":[9],"Nonparametric":[10],"feature":[11,48,54],"algorithms":[13],"have":[14],"more":[15,34],"advantages":[16],"than":[17,36],"parametric":[18],"ones":[19],"and":[20,68,112,131],"are":[21],"well":[22],"suited":[23],"for":[24],"nonnormally":[25],"distributed":[26],"data":[27,120],"along":[28],"with":[29],"being":[30],"able":[31],"to":[32],"extract":[33],"features":[35,94],"the":[37,61,66,88,101,109,128,144],"classic":[38],"linear":[39],"discriminant":[40],"analysis.":[41],"In":[42],"this":[43],"paper,":[44],"a":[45,79],"novel":[46],"nonparametric":[47,53],"method,":[50],"namely,":[51],"cosine-based":[52],"(CNFE),":[56],"is":[57,72,95,99,114],"proposed,":[58],"which":[60,98],"weight":[62],"function":[63],"embedded":[64],"within-class":[67],"between-class":[69],"scatter":[70],"matrices":[71],"developed":[73],"based":[74,86],"on":[75,87,136],"cosine":[76],"distance.":[77],"Moreover,":[78],"powerful":[80],"K-nearest":[81],"neighbor":[82],"(KNN)":[83],"classification":[84],"algorithm":[85],"distance":[89],"metric":[90],"formed":[91],"by":[92,116],"CNFE":[93,111,130],"also":[96],"developed,":[97],"called":[100],"CNFE-based":[102],"KNN":[103],"(CKNN)":[104],"classifier.":[105],"The":[106,122],"effectiveness":[107],"of":[108,139],"proposed":[110,129],"CKNN":[113,132],"evaluated":[115],"two":[117],"real":[119],"sets.":[121],"experimental":[123],"results":[124],"demonstrate":[125],"that":[126],"both":[127],"achieve":[133],"remarkable":[134],"performances":[135],"various":[137],"types":[138],"training":[140],"sample":[141],"sizes,":[142],"including":[143],"small-sample-size":[145],"cases.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
