{"id":"https://openalex.org/W3174526971","doi":"https://doi.org/10.1109/icccsp52374.2021.9465345","title":"Detection of Electronic Devices in real images using Deep Learning Techniques","display_name":"Detection of Electronic Devices in real images using Deep Learning Techniques","publication_year":2021,"publication_date":"2021-05-24","ids":{"openalex":"https://openalex.org/W3174526971","doi":"https://doi.org/10.1109/icccsp52374.2021.9465345","mag":"3174526971"},"language":"en","primary_location":{"id":"doi:10.1109/icccsp52374.2021.9465345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","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/A5018456979","display_name":"G Krijeshan","orcid":null},"institutions":[{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]},{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Krijeshan G","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000058503","display_name":"P Raghul","orcid":null},"institutions":[{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]},{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raghul P","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028158559","display_name":"N N Nachiappan","orcid":null},"institutions":[{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]},{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nachiappan N N","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049585848","display_name":"A. Beulah","orcid":null},"institutions":[{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]},{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. Beulah","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108727746","display_name":"R. Priyadharshini","orcid":null},"institutions":[{"id":"https://openalex.org/I20107917","display_name":"Sri Ramachandra Institute of Higher Education and Research","ror":"https://ror.org/0108gdg43","country_code":"IN","type":"education","lineage":["https://openalex.org/I20107917"]},{"id":"https://openalex.org/I916357946","display_name":"Sri Sivasubramaniya Nadar College of Engineering","ror":"https://ror.org/054psm803","country_code":null,"type":"education","lineage":["https://openalex.org/I916357946"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Priyadharshini","raw_affiliation_strings":["Sri Sivasubramaniya Nadar College of Engineering, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Sri Sivasubramaniya Nadar College of Engineering, Chennai, India","institution_ids":["https://openalex.org/I916357946","https://openalex.org/I20107917"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018456979"],"corresponding_institution_ids":["https://openalex.org/I20107917","https://openalex.org/I916357946"],"apc_list":null,"apc_paid":null,"fwci":0.2882,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.54627451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"295","last_page":"300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.998199999332428,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/computer-science","display_name":"Computer science","score":0.8440994024276733},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.8186311721801758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7880628108978271},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7529683709144592},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6691579222679138},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5337828993797302},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5029651522636414},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5023989677429199},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49687984585762024},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4883274734020233},{"id":"https://openalex.org/keywords/object-class-detection","display_name":"Object-class detection","score":0.4639178514480591},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43102771043777466},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3839532434940338},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36702632904052734},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.331359326839447},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.23044756054878235},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.07233437895774841}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8440994024276733},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.8186311721801758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7880628108978271},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7529683709144592},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6691579222679138},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5337828993797302},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5029651522636414},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5023989677429199},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49687984585762024},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4883274734020233},{"id":"https://openalex.org/C71681937","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object-class detection","level":5,"score":0.4639178514480591},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43102771043777466},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3839532434940338},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36702632904052734},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.331359326839447},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.23044756054878235},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.07233437895774841},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1109/icccsp52374.2021.9465345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1608462934","https://openalex.org/W2102605133","https://openalex.org/W2161969291","https://openalex.org/W2552758275","https://openalex.org/W2782964444","https://openalex.org/W2791996660","https://openalex.org/W2800816754","https://openalex.org/W2963037989","https://openalex.org/W2964010755","https://openalex.org/W3034024180","https://openalex.org/W3121480429","https://openalex.org/W4246399668","https://openalex.org/W4288083516","https://openalex.org/W6628973269","https://openalex.org/W6729111202","https://openalex.org/W6747551115"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2901758161","https://openalex.org/W4205668735","https://openalex.org/W2949096641"],"abstract_inverted_index":{"Object":[0],"Detection":[1],"from":[2,255],"real":[3],"world":[4],"scenario":[5],"is":[6,183,218],"a":[7,88,104,177,241],"subset":[8],"of":[9,46,54,95,99,149,192,216,262],"Computer":[10],"Vision,":[11],"that":[12,60,125,224,243],"uses":[13,225],"state-of-the-art":[14],"algorithms":[15,59,102,139,171,217],"and":[16,23,42,92,108,120,156,187,257,267],"techniques":[17],"in":[18,27,34,43,80,129,134,154,163],"deep":[19],"learning":[20,58],"to":[21,67,143,184,227,239],"identify":[22,186],"locate":[24],"the":[25,44,52,64,78,84,100,136,147,189,196,201,236],"objects":[26,131,191],"an":[28,81],"image":[29,47,197],"or":[30],"video.":[31],"Latest":[32],"advancements":[33],"Deep":[35,57],"Learning,":[36],"especially":[37],"Convolutional":[38,116],"Neural":[39,117],"Networks":[40,118],"(CNN)":[41],"field":[45],"processing":[48],"has":[49,264],"further":[50],"improved":[51],"process":[53],"object":[55,73,79,85],"detection.":[56],"are":[61],"developed":[62,272],"over":[63],"years":[65],"aim":[66],"solve":[68],"several":[69],"challenges":[70],"associated":[71,168],"with":[72,87,146,151,169,269],"detection":[74,94,109,150,207],"which":[75],"includes":[76],"localizing":[77],"image,":[82],"classifying":[83,130],"correctly":[86],"high":[89,127],"confidence":[90],"score":[91],"realtime":[93,155,253],"objects.":[96,137,229],"The":[97,166,181,247],"performance":[98],"existing":[101],"involves":[103],"tradeoff":[105],"between":[106],"accuracy":[107,128],"speed.":[110],"Algorithms":[111],"like":[112],"Faster":[113,274],"Region":[114],"based":[115],"(R-CNN)":[119],"Single":[121],"Shot":[122],"Detector":[123],"(SSD)":[124],"achieved":[126],"were":[132,140,158],"slow":[133],"detecting":[135],"Such":[138],"not":[141,159],"able":[142],"keep":[144],"up":[145],"pace":[148],"video":[152],"input":[153,254],"thus":[157,205],"suitable":[160],"for":[161],"implementation":[162],"critical":[164],"applications.":[165],"drawbacks":[167],"these":[170],"can":[172],"be":[173],"eliminated":[174],"by":[175,194],"following":[176],"unified":[178],"one-state":[179],"approach.":[180],"approach":[182,204],"fully":[185],"classify":[188],"required":[190],"interest":[193],"passing":[195],"only":[198],"once":[199],"through":[200],"network.":[202],"This":[203],"decreases":[206],"time":[208],"considerably.":[209],"You":[210],"Only":[211],"Look":[212],"Once":[213],"(YOLO)":[214],"family":[215],"one":[219],"such":[220],"single":[221],"shot":[222],"detector":[223],"CNNs":[226],"detect":[228],"In":[230],"our":[231],"work,":[232],"we":[233],"have":[234],"used":[235],"YOLOv3":[237,263],"algorithm":[238],"develop":[240],"model":[242,248,271],"detects":[244],"electronic":[245],"devices.":[246],"was":[249],"also":[250],"tested":[251],"against":[252],"webcam":[256],"mean":[258],"Average":[259],"Precision":[260],"(mAP)":[261],"been":[265],"computed":[266],"compared":[268],"another":[270],"using":[273],"R-CNN.":[275]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}