{"id":"https://openalex.org/W3119197739","doi":"https://doi.org/10.1109/icarcv50220.2020.9305397","title":"Improved Deep Learning Method to Fast Detect Vehicles Driving on a Long Span Cable-Stayed Bridge","display_name":"Improved Deep Learning Method to Fast Detect Vehicles Driving on a Long Span Cable-Stayed Bridge","publication_year":2020,"publication_date":"2020-12-13","ids":{"openalex":"https://openalex.org/W3119197739","doi":"https://doi.org/10.1109/icarcv50220.2020.9305397","mag":"3119197739"},"language":"en","primary_location":{"id":"doi:10.1109/icarcv50220.2020.9305397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","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/A5106666841","display_name":"Shuying Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuying Zhang","raw_affiliation_strings":["Highway school, Chang'an University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Highway school, Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338728","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0003-2963-9476"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Wang","raw_affiliation_strings":["School of Electronics and Control Engineering, Chang'an University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Control Engineering, Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039534463","display_name":"Gan Yang","orcid":"https://orcid.org/0000-0002-5018-793X"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gan Yang","raw_affiliation_strings":["Highway School, Chang'an University, China"],"affiliations":[{"raw_affiliation_string":"Highway School, Chang'an University, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055881494","display_name":"Wanshui Han","orcid":"https://orcid.org/0000-0002-9064-4509"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanshui Han","raw_affiliation_strings":["Highway School, Chang'an University, China"],"affiliations":[{"raw_affiliation_string":"Highway School, Chang'an University, China","institution_ids":["https://openalex.org/I25355098"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5106666841"],"corresponding_institution_ids":["https://openalex.org/I25355098"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.20297073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T12740","display_name":"Gait Recognition and Analysis","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/bridge","display_name":"Bridge (graph theory)","score":0.8176775574684143},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7529933452606201},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5281945466995239},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5214332938194275},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5056638717651367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5003018379211426},{"id":"https://openalex.org/keywords/span","display_name":"Span (engineering)","score":0.4421401023864746},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4215732216835022},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.40382421016693115},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.20771634578704834},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18247246742248535},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15668028593063354}],"concepts":[{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.8176775574684143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529933452606201},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5281945466995239},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5214332938194275},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5056638717651367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5003018379211426},{"id":"https://openalex.org/C2778753569","wikidata":"https://www.wikidata.org/wiki/Q1960395","display_name":"Span (engineering)","level":2,"score":0.4421401023864746},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4215732216835022},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.40382421016693115},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.20771634578704834},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18247246742248535},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15668028593063354},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icarcv50220.2020.9305397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icarcv50220.2020.9305397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G5948456080","display_name":null,"funder_award_id":"2019YFB1600700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8150890666","display_name":null,"funder_award_id":"51505037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8238719222","display_name":null,"funder_award_id":"300102320305","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1902950398","https://openalex.org/W2018186867","https://openalex.org/W2025586229","https://openalex.org/W2037117813","https://openalex.org/W2048990152","https://openalex.org/W2102605133","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2796347433","https://openalex.org/W2921276571","https://openalex.org/W2945932553","https://openalex.org/W2950418233","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963420686","https://openalex.org/W2963456480","https://openalex.org/W2964121718","https://openalex.org/W2970974096","https://openalex.org/W3018757597","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6675026286","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"The":[0,56,77,141,171],"dynamic":[1],"load":[2],"on":[3,24,133],"the":[4,10,16,74,86,93,96,107,114,128,159],"bridge":[5,26,33,138,177],"is":[6,14,27,46,60,82,101,144],"normally":[7],"generated":[8],"by":[9,73],"traffic":[11],"flow.":[12],"It":[13],"therefore":[15],"acquisition":[17],"of":[18,28,68,89,109],"spatiotemporal":[19],"information":[20,165],"for":[21],"vehicles":[22],"driving":[23],"a":[25,134],"great":[29],"significance":[30],"to":[31,84,103,106,112,175],"assess":[32],"structures.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38],"proposed":[39,142,160],"an":[40],"improved":[41],"deep":[42],"learning":[43,58],"network,":[44],"which":[45],"inspired":[47],"from":[48,127],"YOLOv4":[49,154],"(You":[50],"only":[51],"look":[52],"once)":[53],"network":[54],"structure.":[55],"transfer":[57],"method":[59,143,161],"applied":[61],"in":[62,139,180],"training,":[63],"and":[64,153,169],"designated":[65],"nine":[66],"sets":[67],"anchor":[69],"values":[70],"are":[71,121],"obtained":[72],"K-means":[75],"clustering.":[76],"Soft-NMS":[78],"(Non-Maximum":[79],"Suppression)":[80],"algorithm":[81],"fused":[83],"improve":[85],"detection":[87],"effect":[88],"overlapping":[90],"targets.":[91],"At":[92],"same":[94],"time,":[95],"SENet":[97],"(Squeeze-and-":[98],"Excitation":[99],"Networks)":[100],"used":[102,132],"assign":[104],"weights":[105],"features":[108],"each":[110],"channel":[111],"learn":[113],"correlation":[115],"between":[116],"different":[117],"channels.":[118],"Data":[119],"set":[120],"established":[122],"with":[123,146],"video":[124],"clips":[125],"cut":[126],"surveillance":[129],"system":[130],"currently":[131],"long":[135],"span":[136],"cable-stayed":[137],"China.":[140],"compared":[145],"SSD":[147],"(Single":[148],"Shot":[149],"MultiBox":[150],"Detector),":[151],"YOLOv3":[152],"algorithms.":[155],"Experimental":[156],"proves":[157],"that":[158],"can":[162],"detect":[163],"vehicle":[164],"more":[166],"accurately,":[167],"efficiently":[168],"stably.":[170],"result":[172],"could":[173],"extend":[174],"other":[176],"monitoring":[178],"applications":[179],"future.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}