{"id":"https://openalex.org/W2205041216","doi":"https://doi.org/10.1109/btas.2015.7358792","title":"Robust biometrics recognition using joint weighted dictionary learning and smoothed L0 norm","display_name":"Robust biometrics recognition using joint weighted dictionary learning and smoothed L0 norm","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2205041216","doi":"https://doi.org/10.1109/btas.2015.7358792","mag":"2205041216"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2015.7358792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2015.7358792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5036641412","display_name":"Rahman Khorsandi","orcid":null},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rahman Khorsandi","raw_affiliation_strings":["Univeristy of Miami"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univeristy of Miami","institution_ids":["https://openalex.org/I83328450"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003192826","display_name":"Ali Taalimi","orcid":null},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Taalimi","raw_affiliation_strings":["University of Tennessee"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tennessee","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108096234","display_name":"Mohamed Abdel-Mottaleb","orcid":null},"institutions":[{"id":"https://openalex.org/I83328450","display_name":"Miami University","ror":"https://ror.org/05nbqxr67","country_code":"US","type":"education","lineage":["https://openalex.org/I83328450"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed Abdel-Mottaleb","raw_affiliation_strings":["Univeristy of Miami"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univeristy of Miami","institution_ids":["https://openalex.org/I83328450"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2428,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42814254,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"54","issue":null,"first_page":"1","last_page":"6"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9954000115394592,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7031821608543396},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.6919888257980347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.646755039691925},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.6455623507499695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6433165669441223},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6343824863433838},{"id":"https://openalex.org/keywords/k-svd","display_name":"K-SVD","score":0.6214594841003418},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4589065611362457},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4383498430252075},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4339962303638458},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42084643244743347},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41786548495292664},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3253384232521057},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26363736391067505},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10810276865959167}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7031821608543396},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.6919888257980347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646755039691925},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.6455623507499695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6433165669441223},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6343824863433838},{"id":"https://openalex.org/C154771677","wikidata":"https://www.wikidata.org/wiki/Q17098361","display_name":"K-SVD","level":3,"score":0.6214594841003418},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4589065611362457},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4383498430252075},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4339962303638458},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42084643244743347},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41786548495292664},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3253384232521057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26363736391067505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10810276865959167},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2015.7358792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2015.7358792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1527059394","https://openalex.org/W1541033069","https://openalex.org/W1963932623","https://openalex.org/W1986620389","https://openalex.org/W2062690810","https://openalex.org/W2070511404","https://openalex.org/W2093427575","https://openalex.org/W2100068253","https://openalex.org/W2101799416","https://openalex.org/W2102129292","https://openalex.org/W2107214962","https://openalex.org/W2107861471","https://openalex.org/W2129812935","https://openalex.org/W2132254548","https://openalex.org/W2132283655","https://openalex.org/W2132559658","https://openalex.org/W2133800322","https://openalex.org/W2142225600","https://openalex.org/W2145525019","https://openalex.org/W2155482699","https://openalex.org/W2160547390","https://openalex.org/W2161969291","https://openalex.org/W2163112044","https://openalex.org/W2167188281","https://openalex.org/W2168010845","https://openalex.org/W2296616510","https://openalex.org/W4250955649","https://openalex.org/W6631547310","https://openalex.org/W6666241238","https://openalex.org/W6679579843"],"related_works":["https://openalex.org/W2509955295","https://openalex.org/W2572092625","https://openalex.org/W1987225540","https://openalex.org/W2116933539","https://openalex.org/W1778286912","https://openalex.org/W2099321050","https://openalex.org/W4245251483","https://openalex.org/W2887640166","https://openalex.org/W2008821896","https://openalex.org/W2152958724"],"abstract_inverted_index":{"In":[0,19,150,176],"this":[1],"paper,":[2],"we":[3,178],"present":[4],"an":[5,100,125],"automated":[6],"system":[7],"for":[8,57,209],"robust":[9],"biometric":[10],"recognition":[11,69,211],"based":[12],"upon":[13],"sparse":[14,20,58],"representation":[15,59],"and":[16,68,133,141,201],"dictionary":[17,89,103,148],"learning.":[18,149],"representation,":[21],"extracted":[22,40],"features":[23,41],"from":[24,94],"the":[25,39,43,53,64,79,111,114,120,128,131,136,147,151,159,162,171,190,196,202,214],"training":[26,98],"data":[27,45],"are":[28,143],"used":[29,76],"to":[30,62,110,169,188],"develop":[31],"a":[32,47,86,95,154,185],"dictionary.":[33,54,83,116],"Classification":[34],"is":[35,156,184],"achieved":[36],"by":[37],"representing":[38],"of":[42,50,81,97,119,135,204],"test":[44],"as":[46],"linear":[48],"combination":[49],"entries":[51],"in":[52,66,77,113],"Dictionary":[55],"learning":[56,90],"has":[60],"shown":[61],"improve":[63],"results":[65],"classification":[67],"tasks":[70],"since":[71],"class":[72],"labels":[73],"can":[74],"be":[75],"obtaining":[78],"atoms":[80,112,142,164],"learnt":[82,115],"We":[84],"propose":[85],"joint":[87],"weighted":[88],"which":[91,183],"simultaneously":[92],"learns":[93],"set":[96],"samples":[99],"over":[101],"complete":[102],"along":[104],"with":[105,124],"weight":[106,121,139],"vectors":[107,140],"that":[108,165,213],"correspond":[109],"The":[117,138],"components":[118],"vector":[122],"associated":[123],"atom":[126,132],"represent":[127,166],"relationship":[129],"between":[130,161,173],"each":[134],"classes.":[137],"jointly":[144],"obtained":[145,163],"during":[146],"proposed":[152,215],"method,":[153],"constraint":[155],"imposed":[157],"on":[158,195],"correlation":[160],"different":[167],"classes":[168],"decrease":[170],"similarity":[172],"these":[174],"atoms.":[175],"addition,":[177],"use":[179],"smoothed":[180],"L0":[181],"norm":[182],"fast":[186],"algorithm":[187],"find":[189],"sparsest":[191],"solution.":[192],"Experiments":[193],"conducted":[194],"West":[197],"Virginia":[198],"University":[199,203],"(WVU)":[200],"Notre":[205],"Dame":[206],"(UND)":[207],"datasets":[208],"ear":[210],"show":[212],"method":[216],"outperforms":[217],"other":[218],"state-of-the-art":[219],"classifiers.":[220]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}