{"id":"https://openalex.org/W4312284951","doi":"https://doi.org/10.1145/3548608.3559279","title":"Application of Dense Crowd Detection Method Based on Lightweight Neural Network in Subway Crowd Recognition","display_name":"Application of Dense Crowd Detection Method Based on Lightweight Neural Network in Subway Crowd Recognition","publication_year":2022,"publication_date":"2022-06-24","ids":{"openalex":"https://openalex.org/W4312284951","doi":"https://doi.org/10.1145/3548608.3559279"},"language":"en","primary_location":{"id":"doi:10.1145/3548608.3559279","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548608.3559279","pdf_url":null,"source":{"id":"https://openalex.org/S4363608876","display_name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","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":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","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/A5101444398","display_name":"Jimin Liu","orcid":"https://orcid.org/0000-0003-3459-8349"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jimin Liu","raw_affiliation_strings":["College of Intelligent Equipment, Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligent Equipment, Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089547269","display_name":"Junjie Zhou","orcid":"https://orcid.org/0000-0001-7053-4794"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Zhou","raw_affiliation_strings":["College of Computer Science and Engineering, Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101768935","display_name":"Fang Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Fan","raw_affiliation_strings":["College of Intelligent Equipment, Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligent Equipment, Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089562540","display_name":"Chuangsen Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuangsen Xie","raw_affiliation_strings":["College of Intelligent Equipment, Shandong University of Science and Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligent Equipment, Shandong University of Science and Technology, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101444398"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13346642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"644","last_page":"648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.7502709031105042},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.7329744696617126},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6976916193962097},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6122996807098389},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5212984085083008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5161179304122925},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5028071403503418},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.48926231265068054},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.46455806493759155},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4345269203186035},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.41170182824134827},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3855452537536621},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3667764365673065},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.32967281341552734},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15292143821716309},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1475105583667755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7502709031105042},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7329744696617126},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6976916193962097},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6122996807098389},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5212984085083008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5161179304122925},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5028071403503418},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.48926231265068054},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.46455806493759155},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4345269203186035},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.41170182824134827},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3855452537536621},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3667764365673065},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.32967281341552734},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15292143821716309},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1475105583667755},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3548608.3559279","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548608.3559279","pdf_url":null,"source":{"id":"https://openalex.org/S4363608876","display_name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","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":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1981276685","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2570343428","https://openalex.org/W2883363148","https://openalex.org/W2896540732","https://openalex.org/W2963037989","https://openalex.org/W2963681621","https://openalex.org/W3136755741","https://openalex.org/W3137428911","https://openalex.org/W6600347437"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W2964954556"],"abstract_inverted_index":{"With":[0],"the":[1,31,38,42,46,51,62,65,71,74,76,85,90,95,103,109,114,120,141,146],"rapid":[2],"development":[3],"of":[4,16,35,41,64,70,108,137,148],"rail":[5],"transit":[6],"network,":[7,48],"scientific":[8],"and":[9,23,49,68,106,119,139,144],"effective":[10],"urban":[11],"public":[12,21],"transportation":[13,25],"management":[14],"is":[15,82,124],"great":[17],"significance":[18],"to":[19,54,94],"maintaining":[20],"order":[22],"planning":[24],"operations.":[26],"This":[27],"paper":[28],"aims":[29],"at":[30,61],"original":[32,121],"network":[33,58,78,116,138,151],"structure":[34],"YOLOv3,":[36],"deletes":[37],"repeated":[39,104,110],"data":[40,105],"convolution":[43,52,111,122,130],"module":[44,112],"in":[45,73,113,153],"detection":[47,142],"optimizes":[50],"method":[53,123],"design":[55],"a":[56,127],"lightweight":[57,149],"structure.":[59],"Aiming":[60],"problem":[63],"complex":[66],"posture":[67],"background":[69],"crowd":[72,155],"subway,":[75],"Darknet53":[77],"with":[79,126],"better":[80],"performance":[81],"selected":[83],"as":[84],"feature":[86],"extraction":[87],"network.":[88],"At":[89],"same":[91],"time,":[92],"according":[93],"actual":[96],"speed":[97],"requirements":[98],"for":[99],"subway":[100,154],"pedestrian":[101],"detection,":[102],"parameters":[107],"deep":[115],"are":[117],"deleted,":[118],"replaced":[125],"smaller":[128],"depth":[129],"method.":[131],"Thereby":[132],"it":[133],"reduces":[134],"time":[135],"complexity":[136],"improves":[140],"speed,":[143],"achieves":[145],"application":[147],"neural":[150],"model":[152],"recognition.":[156]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
