{"id":"https://openalex.org/W3215199235","doi":"https://doi.org/10.1109/etfa45728.2021.9613245","title":"Computer Vision Based Conveyor Belt Congestion Recognition in Logistics Industrial Parks","display_name":"Computer Vision Based Conveyor Belt Congestion Recognition in Logistics Industrial Parks","publication_year":2021,"publication_date":"2021-09-07","ids":{"openalex":"https://openalex.org/W3215199235","doi":"https://doi.org/10.1109/etfa45728.2021.9613245","mag":"3215199235"},"language":"en","primary_location":{"id":"doi:10.1109/etfa45728.2021.9613245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa45728.2021.9613245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","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/A5100427073","display_name":"Yifan Li","orcid":"https://orcid.org/0009-0005-6092-092X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065649868","display_name":"Yingchun Niu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingchun Niu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102199276","display_name":"Yang Liu","orcid":"https://orcid.org/0009-0004-6858-6738"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["JD Logistics, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600006","display_name":"Li Zheng","orcid":"https://orcid.org/0000-0002-6100-2443"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zheng","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100784344","display_name":"Zichen Wang","orcid":"https://orcid.org/0009-0006-4798-2285"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zichen Wang","raw_affiliation_strings":["JD Logistics, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015611759","display_name":"Wenming Zhe","orcid":"https://orcid.org/0000-0003-1753-5784"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zhe","raw_affiliation_strings":["JD Logistics, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD Logistics, Beijing","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6766,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.66526241,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13341","display_name":"Belt Conveyor Systems Engineering","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T13341","display_name":"Belt Conveyor Systems Engineering","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11814","display_name":"Advanced Manufacturing and Logistics Optimization","score":0.9970999956130981,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.987500011920929,"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":0.6989884376525879},{"id":"https://openalex.org/keywords/conveyor-belt","display_name":"Conveyor belt","score":0.6892774105072021},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.6404423713684082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5033552050590515},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49312469363212585},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.49139395356178284},{"id":"https://openalex.org/keywords/belt-conveyor","display_name":"Belt conveyor","score":0.47301343083381653},{"id":"https://openalex.org/keywords/conveyor-system","display_name":"Conveyor system","score":0.4412741959095001},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.367889940738678},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2021920084953308},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.10499182343482971}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6989884376525879},{"id":"https://openalex.org/C2777709985","wikidata":"https://www.wikidata.org/wiki/Q770135","display_name":"Conveyor belt","level":2,"score":0.6892774105072021},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.6404423713684082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5033552050590515},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49312469363212585},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.49139395356178284},{"id":"https://openalex.org/C2986611964","wikidata":"https://www.wikidata.org/wiki/Q770135","display_name":"Belt conveyor","level":2,"score":0.47301343083381653},{"id":"https://openalex.org/C2780927502","wikidata":"https://www.wikidata.org/wiki/Q577998","display_name":"Conveyor system","level":2,"score":0.4412741959095001},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.367889940738678},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2021920084953308},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.10499182343482971},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/etfa45728.2021.9613245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa45728.2021.9613245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA )","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":25,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1966778069","https://openalex.org/W2067924292","https://openalex.org/W2077243934","https://openalex.org/W2085438354","https://openalex.org/W2125186487","https://openalex.org/W2135508370","https://openalex.org/W2145023731","https://openalex.org/W2171499725","https://openalex.org/W2183341477","https://openalex.org/W2533214323","https://openalex.org/W2789212072","https://openalex.org/W2883890202","https://openalex.org/W2963037989","https://openalex.org/W2964081807","https://openalex.org/W3088927520","https://openalex.org/W3091969926","https://openalex.org/W3110434546","https://openalex.org/W3145389849","https://openalex.org/W6628973269","https://openalex.org/W6680360772","https://openalex.org/W6685266013","https://openalex.org/W6686164453","https://openalex.org/W6741414320","https://openalex.org/W6903705387"],"related_works":["https://openalex.org/W4381149290","https://openalex.org/W2626698638","https://openalex.org/W2372159205","https://openalex.org/W2055387704","https://openalex.org/W2052267905","https://openalex.org/W2037568867","https://openalex.org/W2377607190","https://openalex.org/W2088757132","https://openalex.org/W2126545235","https://openalex.org/W2571541455"],"abstract_inverted_index":{"Various":[0],"automatic":[1,28],"and":[2,55,76,120,148,157],"intelligent":[3],"technologies":[4],"have":[5],"been":[6],"employed":[7],"to":[8,48,82,92],"facilitate":[9],"the":[10,18,24,31,42,49,94,101,106,111,128,134,145],"logistics":[11,32],"operations":[12],"in":[13,30],"recent":[14],"years":[15],"promoted":[16],"by":[17,64],"trend":[19],"of":[20,45,53,70,78,113,159],"industry":[21],"4.0.":[22],"As":[23],"most":[25],"frequently":[26],"used":[27],"equipment":[29],"industrial":[33],"parks,":[34],"conveyor":[35,58,97,114],"belt":[36,115],"plays":[37],"a":[38,68,86],"critical":[39],"role":[40],"on":[41,96,133,153],"efficient":[43],"sorting":[44,140],"packages.":[46,79],"Due":[47],"reasons":[50],"like":[51],"non-ideality":[52],"scheduling":[54],"inappropriate":[56],"operations,":[57],"belts":[59],"can":[60],"potentially":[61],"be":[62],"impacted":[63],"congestion,":[65],"thereby":[66],"inducing":[67],"series":[69],"consequences":[71],"such":[72],"as":[73],"delay,":[74],"lose":[75],"damage":[77],"In":[80],"order":[81],"tackle":[83],"these":[84],"issues,":[85],"computer":[87],"vision-based":[88],"method":[89,108,130],"is":[90,131],"proposed":[91,107,129],"recognize":[93],"congestion":[95,116],"belts.":[98],"Other":[99],"than":[100],"popular":[102],"deep":[103,146],"learning-based":[104],"techniques,":[105],"comprehensively":[109],"analyzes":[110],"characteristics":[112],"using":[117],"statistical":[118],"approaches":[119],"extract":[121],"informative":[122],"features":[123],"for":[124],"decision":[125],"making.":[126],"Finally,":[127],"evaluated":[132],"data":[135],"collected":[136],"from":[137],"real":[138],"package":[139],"scenarios,":[141],"where":[142],"it":[143],"outperforms":[144],"learning":[147],"conventional":[149],"pattern":[150],"recognition-based":[151],"methods":[152],"both":[154],"detection":[155],"accuracy":[156],"capability":[158],"generalization.":[160]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}