{"id":"https://openalex.org/W4205501745","doi":"https://doi.org/10.1109/bigdata52589.2021.9671658","title":"Lightweight video analytics for cycle time detection in manufacturing","display_name":"Lightweight video analytics for cycle time detection in manufacturing","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205501745","doi":"https://doi.org/10.1109/bigdata52589.2021.9671658"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671658","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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/A5104023096","display_name":"Andrew Walker","orcid":null},"institutions":[{"id":"https://openalex.org/I86725329","display_name":"Hitachi Global Storage Technologies (United States)","ror":"https://ror.org/02q0s1x22","country_code":"US","type":"company","lineage":["https://openalex.org/I86725329"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Walker","raw_affiliation_strings":["IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA","institution_ids":["https://openalex.org/I86725329"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043141175","display_name":"Daisuke Maeda","orcid":"https://orcid.org/0000-0003-4911-401X"},"institutions":[{"id":"https://openalex.org/I86725329","display_name":"Hitachi Global Storage Technologies (United States)","ror":"https://ror.org/02q0s1x22","country_code":"US","type":"company","lineage":["https://openalex.org/I86725329"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daisuke Maeda","raw_affiliation_strings":["IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA","institution_ids":["https://openalex.org/I86725329"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065858508","display_name":"Joydeep Acharya","orcid":null},"institutions":[{"id":"https://openalex.org/I86725329","display_name":"Hitachi Global Storage Technologies (United States)","ror":"https://ror.org/02q0s1x22","country_code":"US","type":"company","lineage":["https://openalex.org/I86725329"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joydeep Acharya","raw_affiliation_strings":["IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA"],"affiliations":[{"raw_affiliation_string":"IoT Edge Lab Hitachi America, Ltd., Santa Clara, CA, USA","institution_ids":["https://openalex.org/I86725329"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104023096"],"corresponding_institution_ids":["https://openalex.org/I86725329"],"apc_list":null,"apc_paid":null,"fwci":0.8849,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72276215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3615","last_page":"3618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9901999831199646,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.761913537979126},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7043003439903259},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5505797266960144},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.5422835946083069},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5380231142044067},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4936695992946625},{"id":"https://openalex.org/keywords/factory","display_name":"Factory (object-oriented programming)","score":0.4564407765865326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3951832056045532},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.35016483068466187},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.19741785526275635},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17147621512413025},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.10855254530906677}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.761913537979126},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7043003439903259},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5505797266960144},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5422835946083069},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5380231142044067},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4936695992946625},{"id":"https://openalex.org/C40149104","wikidata":"https://www.wikidata.org/wiki/Q5620977","display_name":"Factory (object-oriented programming)","level":2,"score":0.4564407765865326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3951832056045532},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.35016483068466187},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.19741785526275635},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17147621512413025},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.10855254530906677},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/bigdata52589.2021.9671658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671658","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","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":19,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2899771611","https://openalex.org/W2963037989","https://openalex.org/W3007102575","https://openalex.org/W3015666110","https://openalex.org/W3017720822","https://openalex.org/W3023716616","https://openalex.org/W3034527633","https://openalex.org/W3096000766","https://openalex.org/W3130568194","https://openalex.org/W3183962526","https://openalex.org/W4230591936","https://openalex.org/W4288092575","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6739901393","https://openalex.org/W6756040250","https://openalex.org/W6769158158","https://openalex.org/W6777126955"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W3158763334","https://openalex.org/W2013981730"],"abstract_inverted_index":{"In":[0,37],"manufacturing,":[1],"manual":[2],"processes":[3],"along":[4],"an":[5,93],"assembly":[6],"line":[7,54],"can":[8,22,70,111,128],"have":[9],"considerable":[10],"productivity":[11],"fluctuations.":[12],"Cycle":[13],"time,":[14],"or":[15],"the":[16,31,52,57,74,80,113,137],"length":[17],"of":[18,34,59,79,125,134,142],"a":[19,26,35,42,96,101,105,119,123],"certain":[20],"process,":[21],"be":[23],"used":[24],"as":[25,63,65],"diagnostic":[27],"tool":[28],"in":[29,73,100,132],"understanding":[30],"performance":[32,145],"degradation":[33],"line.":[36],"this":[38],"paper":[39],"we":[40],"propose":[41],"multi-task":[43],"classification":[44],"model":[45],"that":[46,69,110,127],"leverages":[47],"RGB":[48],"camera":[49],"data":[50],"from":[51],"production":[53],"to":[55],"solve":[56],"problem":[58],"cycle":[60,75,114],"time":[61],"detection,":[62],"well":[64,131],"giving":[66],"additional":[67],"information":[68],"explain":[71],"variations":[72],"time.":[76,115,147],"The":[77],"design":[78],"IoT":[81],"architecture":[82],"required":[83],"for":[84],"our":[85],"video-based":[86],"solution":[87],"is":[88,140],"also":[89,129],"considered.":[90],"We":[91],"conduct":[92],"experiment":[94],"at":[95],"soldering":[97],"inspection":[98],"process":[99],"factory":[102],"by":[103],"building":[104],"computer":[106],"vision":[107],"ML":[108],"module":[109],"estimate":[112],"Our":[116],"results":[117],"show":[118],"competitive":[120],"advantage":[121],"over":[122,146],"benchmark":[124],"YOLO":[126],"work":[130],"spite":[133],"occlusion":[135],"within":[136],"environment":[138],"and":[139],"capable":[141],"maintaining":[143],"strong":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
