{"id":"https://openalex.org/W2886858945","doi":"https://doi.org/10.1145/3230820.3230832","title":"Learning LogDet Divergence for Ear Recognition","display_name":"Learning LogDet Divergence for Ear Recognition","publication_year":2018,"publication_date":"2018-05-16","ids":{"openalex":"https://openalex.org/W2886858945","doi":"https://doi.org/10.1145/3230820.3230832","mag":"2886858945"},"language":"en","primary_location":{"id":"doi:10.1145/3230820.3230832","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3230820.3230832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 2nd International Conference on Biometric Engineering and Applications","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/A5040546817","display_name":"Ibrahim Omara","orcid":"https://orcid.org/0000-0003-3243-990X"},"institutions":[{"id":"https://openalex.org/I63601056","display_name":"Menoufia University","ror":"https://ror.org/05sjrb944","country_code":"EG","type":"education","lineage":["https://openalex.org/I63601056"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN","EG"],"is_corresponding":true,"raw_author_name":"Ibrahim Omara","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China, Department of Mathematics, Menoufia University, Menoufia, Egypt"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China, Department of Mathematics, Menoufia University, Menoufia, Egypt","institution_ids":["https://openalex.org/I63601056","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065505212","display_name":"Ahmed Hagag","orcid":"https://orcid.org/0000-0003-2631-1846"},"institutions":[{"id":"https://openalex.org/I2801005815","display_name":"Egyptian e-Learning University","ror":"https://ror.org/045ms0x79","country_code":"EG","type":"education","lineage":["https://openalex.org/I2801005815"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ahmed Hagag","raw_affiliation_strings":["Department of Information Technology, Egyptian, E-Learning University, Dokki, Giza, Egypt"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Egyptian, E-Learning University, Dokki, Giza, Egypt","institution_ids":["https://openalex.org/I2801005815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636655","display_name":"Wangmeng Zuo","orcid":"https://orcid.org/0000-0002-3330-783X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wangmeng Zuo","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040546817"],"corresponding_institution_ids":["https://openalex.org/I204983213","https://openalex.org/I63601056"],"apc_list":null,"apc_paid":null,"fwci":0.4954,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63356096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"69","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9670000076293945,"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/T11866","display_name":"Reconstructive Facial Surgery Techniques","score":0.9046000242233276,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7622458934783936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7170600891113281},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6709069013595581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6659600138664246},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6577284336090088},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.6541364789009094},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5363045930862427},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5297421216964722},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5073556303977966},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.44454994797706604},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4270697832107544},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.412033349275589},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18681606650352478},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.086864173412323}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7622458934783936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7170600891113281},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6709069013595581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6659600138664246},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6577284336090088},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.6541364789009094},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5363045930862427},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5297421216964722},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5073556303977966},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.44454994797706604},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4270697832107544},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.412033349275589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18681606650352478},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.086864173412323},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3230820.3230832","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3230820.3230832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 2nd International Conference on Biometric Engineering and Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7099999785423279,"display_name":"Reduced inequalities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1764706090","https://openalex.org/W1865963168","https://openalex.org/W1995961871","https://openalex.org/W1996808886","https://openalex.org/W2018713546","https://openalex.org/W2032962413","https://openalex.org/W2043287655","https://openalex.org/W2058001758","https://openalex.org/W2097235937","https://openalex.org/W2103702232","https://openalex.org/W2113366599","https://openalex.org/W2133061702","https://openalex.org/W2136395383","https://openalex.org/W2137082428","https://openalex.org/W2145520667","https://openalex.org/W2151816796","https://openalex.org/W2157298821","https://openalex.org/W2157684450","https://openalex.org/W2158057578","https://openalex.org/W2163591635","https://openalex.org/W2310200922","https://openalex.org/W2321462649","https://openalex.org/W2405680777","https://openalex.org/W2503002132","https://openalex.org/W2514810124","https://openalex.org/W2545782514","https://openalex.org/W2618126273","https://openalex.org/W2726994734","https://openalex.org/W2791769710","https://openalex.org/W4230485437","https://openalex.org/W4230824908"],"related_works":["https://openalex.org/W4382795578","https://openalex.org/W2355463328","https://openalex.org/W2402648945","https://openalex.org/W1431147547","https://openalex.org/W2771741613","https://openalex.org/W2055761197","https://openalex.org/W2053213469","https://openalex.org/W2057608111","https://openalex.org/W2793032185","https://openalex.org/W939486154"],"abstract_inverted_index":{"Ear-print":[0],"has":[1],"become":[2],"one":[3],"of":[4,9,58],"the":[5,94,132],"most":[6],"important":[7],"types":[8],"vital":[10],"biometric":[11],"in":[12,18,22],"recent":[13],"years;":[14],"ear-print":[15],"is":[16,75,90],"using":[17],"different":[19],"applications;":[20],"especially":[21],"forensic":[23],"science.":[24],"In":[25,49],"this":[26],"paper,":[27],"we":[28],"present":[29],"a":[30,99],"novel":[31],"approach":[32,128],"for":[33,41,47,77,102,147],"ear":[34,67,95],"recognition":[35,139],"based":[36,87],"on":[37,113],"fusion":[38,78],"local":[39],"descriptors":[40],"feature":[42,54],"extraction,":[43],"and":[44,56,81,121,135,145,152],"LogDot":[45,85],"divergence":[46,86],"classification.":[48],"details,":[50],"binarized":[51],"statistical":[52],"image":[53],"(BSIF)":[55],"patterns":[57],"oriented":[59],"edge":[60],"magnitude":[61],"(POEM)":[62],"are":[63],"used":[64],"to":[65,92],"represent":[66],"image.":[68],"Then,":[69],"discriminative":[70],"correlation":[71],"analysis":[72],"(DCA)":[73],"algorithm":[74],"exploited":[76],"those":[79],"features":[80],"reduction":[82],"dimension.":[83],"Finally,":[84],"metric":[88],"learning":[89,98],"adopted":[91],"recognize":[93],"images":[96],"by":[97],"Mahalanobis":[100],"matrix":[101],"approximate":[103],"nearest":[104],"neighbor":[105],"(ANN)":[106],"approach.":[107],"The":[108,126],"experimental":[109],"results":[110],"ar":[111],"performed":[112],"four":[114],"available":[115],"datasets;":[116],"IIT":[117,148],"Delhi":[118,149],"I,":[119,123,150,154],"II":[120,124],"USTB":[122,153],"datasets.":[125],"proposed":[127],"superior":[129],"performance":[130],"over":[131],"state-of-the-art":[133],"approaches":[134],"can":[136],"achieve":[137],"promising":[138],"rates":[140],"around":[141],"98.4%,":[142],"98.7%,":[143],"100%":[144],"97.4%":[146],"II,":[151,155],"respectively.":[156]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
