{"id":"https://openalex.org/W2107457018","doi":"https://doi.org/10.1109/ijcnn.2004.1381049","title":"A face detection system using shunting inhibitory convolutional neural networks","display_name":"A face detection system using shunting inhibitory convolutional neural networks","publication_year":2005,"publication_date":"2005-02-28","ids":{"openalex":"https://openalex.org/W2107457018","doi":"https://doi.org/10.1109/ijcnn.2004.1381049","mag":"2107457018"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1381049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","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/A5088693326","display_name":"Fok Hing Chi Tivive","orcid":"https://orcid.org/0000-0001-8961-2289"},"institutions":[{"id":"https://openalex.org/I12079687","display_name":"Edith Cowan University","ror":"https://ror.org/05jhnwe22","country_code":"AU","type":"education","lineage":["https://openalex.org/I12079687"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"F.H.C. Tivive","raw_affiliation_strings":["School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia","[School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia]"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia","institution_ids":["https://openalex.org/I12079687"]},{"raw_affiliation_string":"[School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia]","institution_ids":["https://openalex.org/I12079687"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072662577","display_name":"Abdesselam Bouzerdoum","orcid":"https://orcid.org/0000-0002-9163-0045"},"institutions":[{"id":"https://openalex.org/I12079687","display_name":"Edith Cowan University","ror":"https://ror.org/05jhnwe22","country_code":"AU","type":"education","lineage":["https://openalex.org/I12079687"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. Bouzerdoum","raw_affiliation_strings":["School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia","[School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia]"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia","institution_ids":["https://openalex.org/I12079687"]},{"raw_affiliation_string":"[School of Engineering and Mathematics, Edith Cowan University, Perth, WA, Australia]","institution_ids":["https://openalex.org/I12079687"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088693326"],"corresponding_institution_ids":["https://openalex.org/I12079687"],"apc_list":null,"apc_paid":null,"fwci":1.7624,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.86231025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"4","issue":null,"first_page":"2571","last_page":"2575"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9821000099182129,"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":0.9821000099182129,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9818999767303467,"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/T10860","display_name":"Speech and Audio Processing","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7811593413352966},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7211109399795532},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6997365355491638},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6798295974731445},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.5803067684173584},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5746369957923889},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5598776340484619},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.5316662788391113},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44755980372428894},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4191516935825348},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41540804505348206},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4150947332382202}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7811593413352966},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7211109399795532},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6997365355491638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6798295974731445},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.5803067684173584},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5746369957923889},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5598776340484619},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.5316662788391113},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44755980372428894},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4191516935825348},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41540804505348206},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4150947332382202},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2004.1381049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381049","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5899999737739563,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1656096371","https://openalex.org/W2010197352","https://openalex.org/W2095809036","https://openalex.org/W2099725280","https://openalex.org/W2125264278","https://openalex.org/W2152072489","https://openalex.org/W2159686933","https://openalex.org/W2217896605","https://openalex.org/W2466644873","https://openalex.org/W6688992846","https://openalex.org/W6719706700"],"related_works":["https://openalex.org/W1983393909","https://openalex.org/W2040150569","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W1911540634","https://openalex.org/W2336272890","https://openalex.org/W2013909972","https://openalex.org/W4308999381","https://openalex.org/W3183843611","https://openalex.org/W4312238398"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,8,27,44,76,91,98,158],"face":[3,57,81,116,140,159],"detection":[4,67,117,160,166],"system":[5,118,129],"based":[6,47,74,109,121],"on":[7,48,75,90,110,122],"class":[9],"of":[10,23,79,134,148],"convolutional":[11,17,125,152],"neural":[12,18,126,153],"networks,":[13],"namely":[14],"shunting":[15],"inhibitory":[16],"networks":[19,25],"(SICoNNets).":[20],"The":[21,128,165],"topology":[22],"these":[24],"is":[26,119,155],"flexible":[28],"feedforward":[29],"architecture":[30],"with":[31,103],"three":[32,62],"different":[33,149,163,169],"connections":[34],"schemes:":[35],"fully-connected,":[36],"toeplitz-connected":[37,86],"and":[38,51,58,82,95,137],"binary-connected.":[39],"SICoNNets":[40],"were":[41],"trained,":[42],"using":[43],"hybrid":[45],"method":[46],"Rprop,":[49],"Quickprop":[50],"least":[52],"squares,":[53],"to":[54,174],"discriminate":[55],"between":[56],"non-face":[59,83],"patterns.":[60,84],"All":[61],"connection":[63],"schemes":[64],"achieve":[65],"99%":[66,99],"accuracy":[68],"at":[69,162],"5%":[70],"false":[71,106],"alarm":[72,107],"rate,":[73],"test":[77,113],"set":[78,94],"7000":[80],"Furthermore,":[85],"network":[87,154],"was":[88],"trained":[89,124],"larger":[92],"training":[93],"has":[96],"achieved":[97],"correct":[100],"classification":[101],"rate":[102,108],"only":[104],"1%":[105],"the":[111,123,139,143,151,176],"same":[112],"set.":[114],"A":[115],"built":[120],"networks.":[127],"accepts":[130],"an":[131],"input":[132],"image":[133],"arbitrary":[135],"size":[136],"localizes":[138],"patterns":[141],"in":[142],"image.":[144],"To":[145],"localize":[146],"faces":[147],"sizes,":[150],"applied":[156],"as":[157],"filter":[161],"scales.":[164],"scores":[167],"from":[168],"scales":[170],"are":[171],"aggregated":[172],"together":[173],"form":[175],"final":[177],"decision.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
