{"id":"https://openalex.org/W2290420786","doi":"https://doi.org/10.1186/s13634-016-0328-0","title":"Class-specific kernel linear regression classification for face recognition under low-resolution and illumination variation conditions","display_name":"Class-specific kernel linear regression classification for face recognition under low-resolution and illumination variation conditions","publication_year":2016,"publication_date":"2016-02-27","ids":{"openalex":"https://openalex.org/W2290420786","doi":"https://doi.org/10.1186/s13634-016-0328-0","mag":"2290420786"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-016-0328-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0328-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0328-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0328-0","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072828215","display_name":"Yang\u2010Ting Chou","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yang-Ting Chou","raw_affiliation_strings":["Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111982476","display_name":"Shih-Ming Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shih-Ming Huang","raw_affiliation_strings":["Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068393966","display_name":"Jar-Ferr Yang","orcid":"https://orcid.org/0000-0001-6502-9961"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jar-Ferr Yang","raw_affiliation_strings":["Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0001-6502-9961","affiliations":[{"raw_affiliation_string":"Institute of Computer and Communication EngineeringDepartment of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072828215"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":1.0135,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.82408063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"2016","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9714999794960022,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9611999988555908,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6886072754859924},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6536149978637695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5991141200065613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5631963610649109},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.561596155166626},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.5175868272781372},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4344802796840668},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4209638237953186},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.41875821352005005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4141445755958557},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.30048173666000366},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.23233941197395325}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6886072754859924},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6536149978637695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5991141200065613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5631963610649109},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.561596155166626},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.5175868272781372},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4344802796840668},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4209638237953186},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.41875821352005005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4141445755958557},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30048173666000366},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.23233941197395325},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1186/s13634-016-0328-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0328-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0328-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1186/s13634-016-0328-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-016-0328-0","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-016-0328-0","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4099999964237213,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6073558875","display_name":null,"funder_award_id":"NSC 103-2221-E-006-109-MY3","funder_id":"https://openalex.org/F4320321040","funder_display_name":"National Science Council"}],"funders":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2290420786.pdf","grobid_xml":"https://content.openalex.org/works/W2290420786.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1545641654","https://openalex.org/W1591385104","https://openalex.org/W1975815261","https://openalex.org/W1976268016","https://openalex.org/W1983350937","https://openalex.org/W1987856859","https://openalex.org/W1989248792","https://openalex.org/W1989702938","https://openalex.org/W2008107235","https://openalex.org/W2014697905","https://openalex.org/W2021012145","https://openalex.org/W2033419168","https://openalex.org/W2035277592","https://openalex.org/W2035475513","https://openalex.org/W2041657594","https://openalex.org/W2045591889","https://openalex.org/W2054515210","https://openalex.org/W2069498936","https://openalex.org/W2089122605","https://openalex.org/W2096348128","https://openalex.org/W2097486709","https://openalex.org/W2098951409","https://openalex.org/W2101043704","https://openalex.org/W2103056131","https://openalex.org/W2103250033","https://openalex.org/W2108995755","https://openalex.org/W2114380981","https://openalex.org/W2117553576","https://openalex.org/W2117711690","https://openalex.org/W2118328928","https://openalex.org/W2121647436","https://openalex.org/W2122695681","https://openalex.org/W2123921160","https://openalex.org/W2126653386","https://openalex.org/W2129680231","https://openalex.org/W2129812935","https://openalex.org/W2131081720","https://openalex.org/W2134262590","https://openalex.org/W2136499149","https://openalex.org/W2138451337","https://openalex.org/W2140095548","https://openalex.org/W2143245774","https://openalex.org/W2146474141","https://openalex.org/W2150796457","https://openalex.org/W2154189032","https://openalex.org/W2155000092","https://openalex.org/W2163647352","https://openalex.org/W2165916500","https://openalex.org/W2167601730","https://openalex.org/W2170984974","https://openalex.org/W2611015177","https://openalex.org/W4241510852","https://openalex.org/W6600553734","https://openalex.org/W6600648412","https://openalex.org/W6823750285"],"related_works":["https://openalex.org/W3123056048","https://openalex.org/W4386075310","https://openalex.org/W2169565408","https://openalex.org/W4389428786","https://openalex.org/W1603091392","https://openalex.org/W2095626363","https://openalex.org/W2089892314","https://openalex.org/W2165576085","https://openalex.org/W2974741803","https://openalex.org/W2420851703"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,40],"novel":[4],"class-specific":[5,93],"kernel":[6,41,70,84,94],"linear":[7,49,98],"regression":[8,50,99],"classification":[9],"is":[10,79],"proposed":[11,92,136],"for":[12,51,88],"face":[13],"recognition":[14],"under":[15,142],"very":[16,147],"low-resolution":[17,25,148],"and":[18,118,129,146],"severe":[19,143],"illumination":[20,29,144],"variation":[21,145],"conditions.":[22,149],"Since":[23],"the":[24,35,45,52,60,69,76,83,91,101,109,135,139],"problem":[26],"coupled":[27],"with":[28,97],"variations":[30],"makes":[31],"ill-posed":[32,53],"data":[33,54],"distribution,":[34],"nonlinear":[36,61,74],"projection":[37,85,95,111],"rendered":[38],"by":[39,67,107],"function":[42,63],"would":[43],"enhance":[44],"modeling":[46],"capability":[47],"of":[48,59],"distribution.":[55],"The":[56],"explicit":[57],"knowledge":[58],"mapping":[62],"can":[64,104],"be":[65,86,105],"avoided":[66],"using":[68],"trick.":[71],"To":[72],"reduce":[73],"redundancy,":[75],"low-rank-r":[77],"approximation":[78],"suggested":[80],"to":[81],"make":[82],"feasible":[87],"classification.":[89],"With":[90],"combined":[96],"classification,":[100],"class":[102],"label":[103],"determined":[106],"calculating":[108],"minimum":[110],"error.":[112],"Experiments":[113],"on":[114],"8":[115,117,119],"\u00d7":[116,120],"6":[121],"images":[122],"down-sampled":[123],"from":[124],"extended":[125],"Yale":[126],"B,":[127],"FERET,":[128],"AR":[130],"facial":[131],"databases":[132],"revealed":[133],"that":[134],"algorithm":[137],"outperforms":[138],"state-of-the-art":[140],"methods":[141]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}