{"id":"https://openalex.org/W2188016474","doi":"https://doi.org/10.1109/icmlc.2015.7340912","title":"Parity symmetrical SRC algorithm for face recognition","display_name":"Parity symmetrical SRC algorithm for face recognition","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2188016474","doi":"https://doi.org/10.1109/icmlc.2015.7340912","mag":"2188016474"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2015.7340912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2015.7340912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-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/A5018880478","display_name":"Xiaoning Song","orcid":"https://orcid.org/0000-0002-3967-4497"},"institutions":[{"id":"https://openalex.org/I111599522","display_name":"Jiangnan University","ror":"https://ror.org/04mkzax54","country_code":"CN","type":"education","lineage":["https://openalex.org/I111599522"]},{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["CN","GB"],"is_corresponding":true,"raw_author_name":"Xiaoning Song","raw_affiliation_strings":["Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, U.K","School of Internet of Things Engineering, Jiangnan University, Wuxi, China"],"affiliations":[{"raw_affiliation_string":"Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]},{"raw_affiliation_string":"School of Internet of Things Engineering, Jiangnan University, Wuxi, China","institution_ids":["https://openalex.org/I111599522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030350248","display_name":"Xibei Yang","orcid":"https://orcid.org/0000-0001-9708-1027"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xibei Yang","raw_affiliation_strings":["School of Computer Science and Engineering, University of Science and Technology, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Science and Technology, Zhenjiang, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018880478"],"corresponding_institution_ids":["https://openalex.org/I111599522","https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09965682,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":null,"first_page":"140","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9950000047683716,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7012415528297424},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6837515830993652},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.596366822719574},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5853469967842102},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5257614254951477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5075958967208862},{"id":"https://openalex.org/keywords/parity","display_name":"Parity (physics)","score":0.49560511112213135},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.488898903131485},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.4611719846725464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4555656909942627},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4309203624725342},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.42030447721481323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30222415924072266},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25941574573516846}],"concepts":[{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7012415528297424},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6837515830993652},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.596366822719574},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5853469967842102},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5257614254951477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5075958967208862},{"id":"https://openalex.org/C2777151079","wikidata":"https://www.wikidata.org/wiki/Q141160","display_name":"Parity (physics)","level":2,"score":0.49560511112213135},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.488898903131485},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.4611719846725464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4555656909942627},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4309203624725342},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.42030447721481323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30222415924072266},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25941574573516846},{"id":"https://openalex.org/C109214941","wikidata":"https://www.wikidata.org/wiki/Q18334","display_name":"Particle physics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/icmlc.2015.7340912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2015.7340912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Machine Learning and Cybernetics (ICMLC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1591385104","https://openalex.org/W1929887928","https://openalex.org/W1974097586","https://openalex.org/W1990319151","https://openalex.org/W2033419168","https://openalex.org/W2039375240","https://openalex.org/W2049234964","https://openalex.org/W2052800689","https://openalex.org/W2069959554","https://openalex.org/W2095176685","https://openalex.org/W2096931164","https://openalex.org/W2102544846","https://openalex.org/W2103560185","https://openalex.org/W2121307414","https://openalex.org/W2122111042","https://openalex.org/W2129812935","https://openalex.org/W2136021407","https://openalex.org/W2141607429","https://openalex.org/W2953119964","https://openalex.org/W4255493559","https://openalex.org/W6635552349","https://openalex.org/W6663996602","https://openalex.org/W6667887326"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W1556451512","https://openalex.org/W1555349535","https://openalex.org/W2167092671","https://openalex.org/W1861706286","https://openalex.org/W4234091740","https://openalex.org/W200201533","https://openalex.org/W4171918","https://openalex.org/W2353047565"],"abstract_inverted_index":{"Although":[0],"the":[1,13,20,68,93,107,121,138,141],"criterion-based":[2],"feature":[3],"extraction":[4],"algorithms":[5,22],"provided":[6],"a":[7,48,62,83,99,103],"feasible":[8],"strategy":[9,57],"to":[10,97],"deal":[11],"with":[12,36,123],"classification":[14,52],"of":[15,19,71,85,106,117,140],"high-dimensional":[16],"data,":[17],"most":[18,108],"existing":[21],"are":[23,89],"locality-oriented":[24],"and":[25,38,112,133],"generally":[26],"suffer":[27],"from":[28,81,120],"many":[29],"issues":[30],"such":[31],"as":[32,102],"uncertainty":[33],"information":[34],"associated":[35],"dataset":[37],"small":[39],"sample":[40,101],"size":[41],"problem.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46],"propose":[47],"novel":[49],"sparse":[50],"representation-based":[51],"method":[53,95],"using":[54,77],"parity":[55,86],"symmetry":[56,70],"for":[58],"face":[59,72,135],"recognition.":[60],"First,":[61],"subspace":[63],"learning":[64],"algorithm":[65],"based":[66],"on":[67,130],"geometric":[69],"image":[73],"is":[74],"developed":[75],"by":[76],"odd-even":[78],"decomposition":[79],"theorem,":[80],"which":[82],"set":[84],"symmetrical":[87],"basis":[88],"constructed":[90],"simultaneously.":[91],"Second,":[92],"proposed":[94,142],"aims":[96],"represent":[98],"query":[100],"linear":[104],"combination":[105],"competitive":[109],"training":[110,118],"samples,":[111],"exploits":[113],"an":[114],"optimal":[115],"representation":[116],"samples":[119],"classes":[122],"major":[124],"relevant":[125],"contributions.":[126],"Experimental":[127],"results":[128],"conducted":[129],"ORL,":[131],"FERET":[132],"AR":[134],"databases":[136],"demonstrate":[137],"effectiveness":[139],"method.":[143]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
