{"id":"https://openalex.org/W7225195307","doi":"https://doi.org/10.37394/232014.2026.22.20","title":"Robust Face Recognition using Sparse Representation with a Novel Greedy Sparse Recovery Technique","display_name":"Robust Face Recognition using Sparse Representation with a Novel Greedy Sparse Recovery Technique","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7225195307","doi":"https://doi.org/10.37394/232014.2026.22.20"},"language":"en","primary_location":{"id":"doi:10.37394/232014.2026.22.20","doi":"https://doi.org/10.37394/232014.2026.22.20","is_oa":true,"landing_page_url":"https://doi.org/10.37394/232014.2026.22.20","pdf_url":null,"source":{"id":"https://openalex.org/S2764930739","display_name":"WSEAS Transactions on Signal Processing archive","issn_l":"1790-5052","issn":["1790-5052","2224-3488"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WSEAS Transactions on Signal Processing","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.37394/232014.2026.22.20","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065044798","display_name":"Rafika Harrabi","orcid":"https://orcid.org/0009-0009-8524-8761","observed_orcids":["https://orcid.org/0009-0009-8524-8761"]},"institutions":[{"id":"https://openalex.org/I72264486","display_name":"University of Tabuk","ror":"https://ror.org/04yej8x59","country_code":"SA","type":"education","lineage":["https://openalex.org/I72264486"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Rafika Harrabi","raw_affiliation_strings":["Faculty of Computers and Information Technology, University of Tabuk, Tabuk 47512, SAUDI ARABIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Computers and Information Technology, University of Tabuk, Tabuk 47512, SAUDI ARABIA","institution_ids":["https://openalex.org/I72264486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5065044798"],"corresponding_institution_ids":["https://openalex.org/I72264486"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80698918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":null,"first_page":"224","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9922000169754028,"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":0.9922000169754028,"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/T11448","display_name":"Face recognition and analysis","score":0.003800000064074993,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.0024999999441206455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/face-recognition","display_name":"face recognition","score":0.9319999814033508},{"id":"https://openalex.org/keywords/sparse-representation","display_name":"sparse representation","score":0.9279999732971191},{"id":"https://openalex.org/keywords/computational-efficiency","display_name":"computational efficiency","score":0.6620000004768372},{"id":"https://openalex.org/keywords/robust-recognition","display_name":"robust recognition","score":0.46399998664855957}],"concepts":[{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.8083999752998352},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7279000282287598},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6115000247955322},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.574999988079071},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5600000023841858},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5370000004768372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5338000059127808},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5249999761581421},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5192999839782715},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5117999911308289},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.40119999647140503},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.37610000371932983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.357699990272522},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2791000008583069},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C188060507","wikidata":"https://www.wikidata.org/wiki/Q653242","display_name":"QR decomposition","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.26089999079704285},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.37394/232014.2026.22.20","doi":"https://doi.org/10.37394/232014.2026.22.20","is_oa":true,"landing_page_url":"https://doi.org/10.37394/232014.2026.22.20","pdf_url":null,"source":{"id":"https://openalex.org/S2764930739","display_name":"WSEAS Transactions on Signal Processing archive","issn_l":"1790-5052","issn":["1790-5052","2224-3488"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WSEAS Transactions on Signal Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.37394/232014.2026.22.20","doi":"https://doi.org/10.37394/232014.2026.22.20","is_oa":true,"landing_page_url":"https://doi.org/10.37394/232014.2026.22.20","pdf_url":null,"source":{"id":"https://openalex.org/S2764930739","display_name":"WSEAS Transactions on Signal Processing archive","issn_l":"1790-5052","issn":["1790-5052","2224-3488"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"WSEAS Transactions on Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1964749215","https://openalex.org/W1969798732","https://openalex.org/W2046658845","https://openalex.org/W2054644753","https://openalex.org/W2079981574","https://openalex.org/W2098012923","https://openalex.org/W2119862467","https://openalex.org/W2120100419","https://openalex.org/W2121647436","https://openalex.org/W2127271355","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2139182243","https://openalex.org/W2148108699","https://openalex.org/W2160979406","https://openalex.org/W2180500047","https://openalex.org/W2288403115","https://openalex.org/W2289917018","https://openalex.org/W2293121884","https://openalex.org/W2293318283","https://openalex.org/W2322044574","https://openalex.org/W2509248648","https://openalex.org/W2513228454","https://openalex.org/W2761508225","https://openalex.org/W2995855127","https://openalex.org/W3022380717","https://openalex.org/W3154776110","https://openalex.org/W4241857088","https://openalex.org/W4308459032","https://openalex.org/W4415878347","https://openalex.org/W7127649807","https://openalex.org/W7128054916","https://openalex.org/W7133134806","https://openalex.org/W7164854359"],"related_works":["https://openalex.org/W2792133273","https://openalex.org/W3154776110","https://openalex.org/W2735049927","https://openalex.org/W2099330163","https://openalex.org/W2115077886","https://openalex.org/W2909501525","https://openalex.org/W3087716834","https://openalex.org/W2367707064","https://openalex.org/W2558098717","https://openalex.org/W2851727350"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3,27,38,151],"efficient":[4],"face":[5],"recognition":[6,87,122],"framework":[7],"based":[8,109],"on":[9,125,128,132],"the":[10,34,54,62,101,107,142],"Fast":[11],"Reduced":[12],"Sampling":[13],"Matching":[14],"Pursuit":[15],"(FRSMP)":[16],"algorithm.":[17],"Unlike":[18],"conventional":[19],"greedy":[20],"sparse":[21,110,146],"recovery":[22],"methods,":[23],"which":[24],"may":[25],"select":[26],"inappropriate":[28],"number":[29],"of":[30,86,100],"components":[31],"per":[32],"iteration,":[33],"proposed":[35,79],"approach":[36],"introduces":[37],"adaptive":[39],"double":[40],"threshold":[41],"mechanism":[42],"to":[43,59],"determine":[44],"relevant":[45],"elements":[46],"in":[47,84],"a":[48],"data-driven":[49],"manner.":[50],"Furthermore,":[51],"it":[52,159],"employs":[53],"Sherman":[55],"Morrison":[56],"Woodbury":[57],"identity":[58],"iteratively":[60],"update":[61],"least":[63],"squares":[64],"solution,":[65],"thereby":[66],"avoiding":[67],"expensive":[68],"large":[69],"scale":[70],"matrix":[71],"inversions":[72],"and":[73,93,96,130,156,163],"significantly":[74],"reducing":[75],"computational":[76,136],"complexity.":[77],"The":[78,138],"method":[80,143],"is":[81],"extensively":[82],"evaluated":[83],"terms":[85],"accuracy,":[88],"execution":[89],"time,":[90],"iteration":[91],"count,":[92],"reconstruction":[94],"error,":[95],"compared":[97],"with":[98,134],"state":[99],"art":[102],"techniques.":[103],"When":[104],"integrated":[105],"into":[106],"kernel":[108],"representation":[111,147],"classification":[112],"(KSRC)":[113],"framework,":[114],"FRSMP":[115],"demonstrates":[116],"notable":[117],"performance":[118],"gains,":[119],"achieving":[120],"high":[121],"rates":[123],"(97.41%":[124],"LFW,":[126],"98.67%":[127],"GT,":[129],"95.37%":[131],"AR)":[133],"reduced":[135],"cost.":[137],"results":[139],"confirm":[140],"that":[141],"outperforms":[144],"existing":[145],"approaches":[148],"while":[149],"maintaining":[150],"effective":[152],"balance":[153],"between":[154],"accuracy":[155],"elliciency,":[157],"making":[158],"suitable":[160],"for":[161],"practical":[162],"resource":[164],"constrained":[165],"applications.":[166]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-04T00:00:00"}