{"id":"https://openalex.org/W4282829254","doi":"https://doi.org/10.1201/9781003340867-7","title":"Smart attendance system","display_name":"Smart attendance system","publication_year":2022,"publication_date":"2022-06-14","ids":{"openalex":"https://openalex.org/W4282829254","doi":"https://doi.org/10.1201/9781003340867-7"},"language":"en","primary_location":{"id":"doi:10.1201/9781003340867-7","doi":"https://doi.org/10.1201/9781003340867-7","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003340867-7","pdf_url":null,"source":{"id":"https://openalex.org/S4306463855","display_name":"Routledge eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319847","host_organization_name":"Routledge","host_organization_lineage":["https://openalex.org/P4310319847","https://openalex.org/P4310320547"],"host_organization_lineage_names":["Routledge","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Application of Communication Computational Intelligence and Learning","raw_type":"book-chapter"},"volume":{"id":"https://openalex.org/W4282834166","display_name":"Application of Communication Computational Intelligence and Learning"},"type":"book-chapter","is_traditional":true,"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/A5101854413","display_name":"Gaurav Kumar Singh","orcid":"https://orcid.org/0000-0001-8728-3936","observed_orcids":["https://orcid.org/0000-0001-8728-3936","https://orcid.org/0009-0009-7801-4721"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaurav Kumar Singh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078462209","display_name":"Grandhi Abhisar","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Grandhi Abhisar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058145709","display_name":"Vaishali V. Ingale","orcid":"https://orcid.org/0009-0008-0224-5139","observed_orcids":["https://orcid.org/0009-0008-0224-5139"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vaishali Ingale","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075248934","display_name":"Prashant Kumar Singh","orcid":"https://orcid.org/0000-0003-3748-5411","observed_orcids":["https://orcid.org/0000-0003-3748-5411"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prashant Kumar Singh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Jatin Kumar","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jatin Kumar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.5512999892234802,"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/T11448","display_name":"Face recognition and analysis","score":0.5512999892234802,"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/T10057","display_name":"Face and Expression Recognition","score":0.4372999966144562,"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/T10828","display_name":"Biometric Identification and Security","score":0.003800000064074993,"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/attendance-tracking","display_name":"attendance tracking","score":0.6309999823570251},{"id":"https://openalex.org/keywords/face-recognition","display_name":"face recognition","score":0.7670000195503235},{"id":"https://openalex.org/keywords/real-time-face-recognition","display_name":"real-time face recognition","score":0.9100000262260437},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"background subtraction","score":0.7559999823570251},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.9620000123977661},{"id":"https://openalex.org/keywords/employee-attendance-management","display_name":"employee attendance management","score":0.6299999952316284},{"id":"https://openalex.org/keywords/leave-management","display_name":"leave management","score":0.4830000102519989},{"id":"https://openalex.org/keywords/biometric-recognition","display_name":"biometric identification","score":0.5170000195503235}],"concepts":[{"id":"https://openalex.org/C2778173179","wikidata":"https://www.wikidata.org/wiki/Q25339289","display_name":"Attendance","level":2,"score":0.4986989498138428},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3736927807331085},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35557690262794495},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.1947842240333557},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/9781003340867-7","doi":"https://doi.org/10.1201/9781003340867-7","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003340867-7","pdf_url":null,"source":{"id":"https://openalex.org/S4306463855","display_name":"Routledge eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319847","host_organization_name":"Routledge","host_organization_lineage":["https://openalex.org/P4310319847","https://openalex.org/P4310320547"],"host_organization_lineage_names":["Routledge","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Application of Communication Computational Intelligence and Learning","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2945995012","https://openalex.org/W2575706248","https://openalex.org/W2724717709","https://openalex.org/W7151242121","https://openalex.org/W2514070389","https://openalex.org/W7166865023","https://openalex.org/W4312811639","https://openalex.org/W4389543348","https://openalex.org/W2971899541","https://openalex.org/W7133820656"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,26,30,71,177,184,255],"the":[3,47,120,160,168,178,190],"performance":[4,219],"of":[5,19,22,49,67,189],"automatic":[6,216],"face":[7,70,100,107,145],"recognition":[8,29,146],"(AFR)":[9],"systems":[10,264],"have":[11,202,236],"made":[12],"them":[13],"widely":[14],"applicable":[15],"for":[16,32,265],"a":[17,37,43,50,60,68,92,133,140,156,196,203,241,256],"variety":[18],"uses,":[20],"most":[21],"which":[23,206],"are":[24,79,240,253],"done":[25],"real-time.":[27],"Face":[28],"real-time":[31],"smart":[33],"attendance":[34,115,267],"is":[35,58,91,108,116,148,155,195,232],"thus":[36],"practical":[38],"application.":[39],"Managing":[40],"employees":[41],"on":[42],"daily":[44],"basis":[45],"necessitates":[46],"use":[48],"system":[51,186],"like":[52],"this.":[53],"Real-time":[54],"image":[55],"background":[56],"subtraction":[57],"still":[59],"challenge,":[61],"making":[62],"this":[63,194,246,249],"operation":[64],"difficult.":[65,131],"Recognition":[66],"human":[69],"real":[72],"time.":[73],"Both":[74],"basic":[75],"and":[76,81,130,147,175,268],"fast":[77],"methods":[78],"used,":[80],"an":[82,227],"analysis":[83,89],"method":[84],"known":[85],"as":[86,187,260],"principal":[87],"component":[88],"(PCA)":[90],"very":[93],"useful":[94,141],"thing":[95],"that":[96,143,158],"helps":[97],"us":[98],"with":[99,245],"matching":[101],"while":[102],"maintaining":[103],"accuracy.":[104],"The":[105,225],"employee\u2019s":[106,161],"used":[109,149],"to":[110,138,150,215,222,262],"track":[111,151],"their":[112,209],"attendance.":[113,153],"Employee":[114],"automatically":[117],"tracked":[118],"by":[119],"technology.":[121],"Manual":[122],"data":[123,183],"entry":[124],"into":[125],"logbooks":[126],"quickly":[127],"becomes":[128],"time-consuming":[129],"As":[132],"result,":[134],"we":[135],"were":[136],"able":[137],"create":[139],"module":[142,157],"includes":[144,159],"employee":[152,211,228],"There":[154,239],"face.":[162],"You\u2019re":[163],"finished":[164],"once":[165],"you\u2019ve":[166],"completed":[167],"enrolment":[169],"form.":[170],"They":[171],"will":[172,201,207],"be":[173,208,223],"photographed":[174],"stored":[176],"database.":[179],"We":[180],"need":[181],"some":[182],"our":[185],"part":[188],"application":[191],"procedure":[192],"because":[193],"one-time":[197],"event.":[198],"Every":[199],"worker":[200],"roll":[204],"number,":[205],"own":[210],"id.":[212],"When":[213],"compared":[214],"performance,":[217],"manual":[218],"was":[220],"found":[221],"inferior.":[224],"time":[226],"spends":[229],"at":[230],"work":[231],"recorded":[233],"after":[234],"they":[235],"been":[237],"identified.":[238],"lot":[242],"more":[243],"choices":[244],"product.":[247],"With":[248],"approach,":[250],"correct":[251],"results":[252],"provided":[254],"user":[257],"interactive":[258],"manner,":[259],"opposed":[261],"traditional":[263],"managing":[266],"leave.":[269]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2022-06-15T00:00:00"}
