{"id":"https://openalex.org/W2804369000","doi":"https://doi.org/10.1109/atsip.2018.8364451","title":"A novel incremental face recognition method based on nonparametric discriminant model","display_name":"A novel incremental face recognition method based on nonparametric discriminant model","publication_year":2018,"publication_date":"2018-03-01","ids":{"openalex":"https://openalex.org/W2804369000","doi":"https://doi.org/10.1109/atsip.2018.8364451","mag":"2804369000"},"language":"en","primary_location":{"id":"doi:10.1109/atsip.2018.8364451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/atsip.2018.8364451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","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/A5014064056","display_name":"Arbia Soula","orcid":null},"institutions":[{"id":"https://openalex.org/I108714496","display_name":"Tunis University","ror":"https://ror.org/02q1spa57","country_code":"TN","type":"education","lineage":["https://openalex.org/I108714496"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Arbia Soula","raw_affiliation_strings":["Signal Images and Information Technologies (LR-SITI-ENIT), University of Tunis E1 Manar, Tunis, TUNISIE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Images and Information Technologies (LR-SITI-ENIT), University of Tunis E1 Manar, Tunis, TUNISIE","institution_ids":["https://openalex.org/I108714496"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002633348","display_name":"Salma Ben Sa\u00efd","orcid":null},"institutions":[{"id":"https://openalex.org/I42731748","display_name":"National Institute of Applied Science and Technology","ror":"https://ror.org/00qn2rd91","country_code":"TN","type":"facility","lineage":["https://openalex.org/I42731748"]},{"id":"https://openalex.org/I63596082","display_name":"Tunis El Manar University","ror":"https://ror.org/029cgt552","country_code":"TN","type":"education","lineage":["https://openalex.org/I63596082"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Salma Ben Said","raw_affiliation_strings":["INSAT, Signal, Images and Information Technologies (LR-SITI-ENIT), University of Tunis El Manar, Tunis, TUNISIE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INSAT, Signal, Images and Information Technologies (LR-SITI-ENIT), University of Tunis El Manar, Tunis, TUNISIE","institution_ids":["https://openalex.org/I63596082","https://openalex.org/I42731748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006211488","display_name":"Riadh Ksantini","orcid":"https://orcid.org/0000-0001-8143-1600"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Riadh Ksantini","raw_affiliation_strings":["SUPCOM: Securite Num\u00e9rique, University of Windsor, Windsor, ON, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SUPCOM: Securite Num\u00e9rique, University of Windsor, Windsor, ON, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063621759","display_name":"Zied Lachiri","orcid":"https://orcid.org/0000-0002-1289-5089"},"institutions":[{"id":"https://openalex.org/I63596082","display_name":"Tunis El Manar University","ror":"https://ror.org/029cgt552","country_code":"TN","type":"education","lineage":["https://openalex.org/I63596082"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Zied Lachiri","raw_affiliation_strings":["Electrical Engineering Departement, Research laboratory SITI, ENIT, University of Tunis El Manar, Tunis, TUNISIE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Departement, Research laboratory SITI, ENIT, University of Tunis El Manar, Tunis, TUNISIE","institution_ids":["https://openalex.org/I63596082"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.424,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66676174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"31","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9990000128746033,"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":0.9990000128746033,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9387999773025513,"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":0.9085000157356262,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7691943645477295},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7682958245277405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6962203979492188},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6454346776008606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6286122798919678},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6135221719741821},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5930114388465881},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.5924513339996338},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5685510039329529},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5466974973678589},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4605393409729004},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4587107300758362},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4508868157863617},{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.4406237006187439},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.42087990045547485},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.41147780418395996},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3182854652404785},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.23242995142936707},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18980440497398376},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.11293509602546692}],"concepts":[{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7691943645477295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7682958245277405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6962203979492188},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6454346776008606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6286122798919678},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6135221719741821},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5930114388465881},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.5924513339996338},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5685510039329529},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5466974973678589},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4605393409729004},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4587107300758362},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4508868157863617},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.4406237006187439},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.42087990045547485},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.41147780418395996},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3182854652404785},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.23242995142936707},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18980440497398376},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.11293509602546692},{"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},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/atsip.2018.8364451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/atsip.2018.8364451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1480487340","https://openalex.org/W1587863168","https://openalex.org/W1770825568","https://openalex.org/W1970748944","https://openalex.org/W1975538958","https://openalex.org/W1989702938","https://openalex.org/W2036070282","https://openalex.org/W2055048367","https://openalex.org/W2065520107","https://openalex.org/W2109002458","https://openalex.org/W2119077463","https://openalex.org/W2120954940","https://openalex.org/W2121451737","https://openalex.org/W2141681031","https://openalex.org/W2149999708","https://openalex.org/W2180187800","https://openalex.org/W2371268217","https://openalex.org/W2516550381","https://openalex.org/W2737715082","https://openalex.org/W3099514962","https://openalex.org/W6681909610"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"Face":[0],"recognition":[1,42,126,150],"has":[2,15],"received":[3],"considerable":[4],"interest":[5],"owing":[6],"to":[7,57,68,90],"its":[8,143],"relevance":[9],"in":[10,18,75,147],"several":[11],"domains.":[12],"Yet,":[13],"it":[14],"some":[16],"difficulties":[17],"many":[19],"real":[20],"world":[21],"applications,":[22],"where":[23],"data":[24],"are":[25,66,73],"collected":[26],"continuously":[27],"and":[28,104,134,145],"must":[29],"be":[30],"updated":[31],"over":[32],"time.":[33],"In":[34],"the":[35,54,82,121,131],"present,":[36],"we":[37],"advance":[38],"an":[39],"adept":[40],"face":[41,125,136],"technique":[43,127],"that":[44,72],"rests":[45],"on":[46,61,130],"Incremental":[47],"Nonparametric":[48],"Discriminant":[49],"Analysis":[50],"(INDA).":[51],"We":[52],"use":[53,101],"Gabor":[55],"wavelet":[56],"extract":[58],"facial":[59],"features":[60],"which":[62],"multi-lob":[63],"ordinal":[64],"filter":[65],"applied":[67],"derive":[69],"Ordinal":[70],"measures":[71],"encoded":[74],"local":[76],"zones,":[77],"as":[78,116],"visual":[79],"parameters.":[80],"Then,":[81],"statistical":[83],"dispersion":[84],"of":[85,102,149],"these":[86],"parameters":[87],"is":[88,97,114],"integrated":[89],"get":[91],"a":[92,117],"feature":[93,112,118],"vector":[94,113],"whose":[95],"dimension":[96],"decreased":[98],"by":[99],"making":[100],"PCA":[103],"variance.":[105],"Last":[106],"but":[107],"not":[108],"least,":[109],"every":[110],"single":[111],"treated":[115],"input":[119],"for":[120],"INDA.":[122],"The":[123],"proffered":[124],"was":[128],"assessed":[129],"well-known":[132],"ORL":[133],"Yale":[135],"databases.":[137],"Experimental":[138],"results":[139],"have":[140],"shown":[141],"clearly":[142],"superiority":[144],"skillfulness":[146],"terms":[148],"performance.":[151]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}