{"id":"https://openalex.org/W3158630962","doi":"https://doi.org/10.1109/iscas51556.2021.9401238","title":"Vol-Net and V3C-Net: Towards End to End Traffic Volume Estimation","display_name":"Vol-Net and V3C-Net: Towards End to End Traffic Volume Estimation","publication_year":2021,"publication_date":"2021-04-27","ids":{"openalex":"https://openalex.org/W3158630962","doi":"https://doi.org/10.1109/iscas51556.2021.9401238","mag":"3158630962"},"language":"en","primary_location":{"id":"doi:10.1109/iscas51556.2021.9401238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5081912019","display_name":"Hood Khizer","orcid":null},"institutions":[{"id":"https://openalex.org/I110357561","display_name":"University of the Sciences","ror":"https://ror.org/048gmay44","country_code":"US","type":"education","lineage":["https://openalex.org/I110357561"]},{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]}],"countries":["PK","US"],"is_corresponding":true,"raw_author_name":"Hood Khizer","raw_affiliation_strings":["National University of Sciences and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Sciences and Technology","institution_ids":["https://openalex.org/I110357561","https://openalex.org/I929597975"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076749679","display_name":"Wahaj Ahmad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wahaj Ahmad","raw_affiliation_strings":["Stech.ai"],"affiliations":[{"raw_affiliation_string":"Stech.ai","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003409263","display_name":"Tayyba Naz","orcid":null},"institutions":[{"id":"https://openalex.org/I110357561","display_name":"University of the Sciences","ror":"https://ror.org/048gmay44","country_code":"US","type":"education","lineage":["https://openalex.org/I110357561"]},{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]}],"countries":["PK","US"],"is_corresponding":false,"raw_author_name":"Tayyba Naz","raw_affiliation_strings":["National University of Sciences and Technology"],"affiliations":[{"raw_affiliation_string":"National University of Sciences and Technology","institution_ids":["https://openalex.org/I110357561","https://openalex.org/I929597975"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079660765","display_name":"Hasan Sajid","orcid":"https://orcid.org/0000-0002-6703-1552"},"institutions":[{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]},{"id":"https://openalex.org/I110357561","display_name":"University of the Sciences","ror":"https://ror.org/048gmay44","country_code":"US","type":"education","lineage":["https://openalex.org/I110357561"]}],"countries":["PK","US"],"is_corresponding":false,"raw_author_name":"Hasan Sajid","raw_affiliation_strings":["National Center of Artificial Intelligence","National University of Sciences and Technology"],"affiliations":[{"raw_affiliation_string":"National Center of Artificial Intelligence","institution_ids":[]},{"raw_affiliation_string":"National University of Sciences and Technology","institution_ids":["https://openalex.org/I110357561","https://openalex.org/I929597975"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081912019"],"corresponding_institution_ids":["https://openalex.org/I110357561","https://openalex.org/I929597975"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04544756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9972000122070312,"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/T10524","display_name":"Traffic control and management","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.7823138236999512},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.7601101398468018},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.549975574016571},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5203810930252075},{"id":"https://openalex.org/keywords/traffic-volume","display_name":"Traffic volume","score":0.5158990621566772},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5129572749137878},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4887857139110565},{"id":"https://openalex.org/keywords/aka","display_name":"AKA","score":0.46951884031295776},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.4482915997505188},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.41976457834243774},{"id":"https://openalex.org/keywords/traffic-analysis","display_name":"Traffic analysis","score":0.41046270728111267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33663851022720337},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.1443905532360077},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1376085877418518},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0835258960723877},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.07867470383644104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7823138236999512},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.7601101398468018},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.549975574016571},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5203810930252075},{"id":"https://openalex.org/C168443057","wikidata":"https://www.wikidata.org/wiki/Q7001223","display_name":"Traffic volume","level":2,"score":0.5158990621566772},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5129572749137878},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4887857139110565},{"id":"https://openalex.org/C121158502","wikidata":"https://www.wikidata.org/wiki/Q4652161","display_name":"AKA","level":2,"score":0.46951884031295776},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.4482915997505188},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.41976457834243774},{"id":"https://openalex.org/C2781317605","wikidata":"https://www.wikidata.org/wiki/Q7832483","display_name":"Traffic analysis","level":2,"score":0.41046270728111267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33663851022720337},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.1443905532360077},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1376085877418518},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0835258960723877},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.07867470383644104},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C161191863","wikidata":"https://www.wikidata.org/wiki/Q199655","display_name":"Library science","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas51556.2021.9401238","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas51556.2021.9401238","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W29773604","https://openalex.org/W1485009520","https://openalex.org/W2033178020","https://openalex.org/W2071860582","https://openalex.org/W2100138625","https://openalex.org/W2139645271","https://openalex.org/W2141896189","https://openalex.org/W2154786377","https://openalex.org/W2535805784","https://openalex.org/W2586934430","https://openalex.org/W2600230189","https://openalex.org/W2600859289","https://openalex.org/W2604593829","https://openalex.org/W2810605094","https://openalex.org/W2964018834","https://openalex.org/W4294391685","https://openalex.org/W6601227349","https://openalex.org/W6735570655"],"related_works":["https://openalex.org/W3171671300","https://openalex.org/W4293088549","https://openalex.org/W570994069","https://openalex.org/W2964663688","https://openalex.org/W3007491104","https://openalex.org/W2187040164","https://openalex.org/W3130174800","https://openalex.org/W639451239","https://openalex.org/W4285292284","https://openalex.org/W1522239898"],"abstract_inverted_index":{"Accurate":[0],"traffic":[1,13,30,34,60,83,104,119,168],"volume":[2,35,120],"estimation":[3,166],"is":[4,113,154],"highly":[5],"important":[6,9],"for":[7,26,130,149,164],"many":[8],"governance":[10],"tasks":[11],"including":[12],"management":[14],"and":[15,46,101,128,142],"city":[16],"planning.":[17],"In":[18,62,85],"this":[19,112,134],"paper,":[20],"we":[21,48,137],"present":[22],"two":[23],"deep":[24,50],"networks":[25,51,80],"counting":[27],"vehicles":[28],"in":[29,121],"video":[31],"streams":[32],"aka":[33],"estimation.":[36],"Unlike":[37],"existing":[38],"approaches":[39],"that":[40,56,160,174],"are":[41,74],"based":[42],"on":[43],"object":[44],"detection":[45],"tracking,":[47],"propose":[49],"to":[52,81,117],"learn":[53],"spatio-temporal":[54],"features":[55,66,96],"can":[57],"directly":[58],"estimate":[59,118],"volume.":[61,84,105,169],"one":[63],"approach,":[64,88],"spatial":[65],"extracted":[67],"by":[68,77],"a":[69,139,145,155],"time-distributed":[70],"convolutional":[71,90],"neural":[72,79,91],"network":[73,92],"temporally":[75],"aggregated":[76],"recurrent":[78],"predict":[82],"the":[86,94,98,103,107,114,131,175,181],"other":[87],"3D":[89],"extracts":[93],"spatiotemporal":[95],"across":[97],"input":[99],"frames":[100],"predicts":[102],"To":[106,125],"best":[108],"of":[109,133,157,167],"our":[110],"knowledge,":[111],"first":[115,156],"attempt":[116],"an":[122],"end-to-end":[123,177],"fashion.":[124],"promote":[126],"research":[127],"development":[129],"solution":[132],"particular":[135],"problem,":[136],"contribute":[138],"challenging":[140],"dataset":[141,153],"therefore,":[143],"establish":[144],"competent":[146],"baseline":[147,182],"method":[148],"comparative":[150],"analysis.":[151],"The":[152],"its":[158],"kind":[159],"provides":[161],"ground":[162],"truths":[163],"direct":[165],"Our":[170],"experimental":[171],"results":[172],"show":[173],"proposed":[176],"methods":[178],"significantly":[179],"outperform":[180],"approach.":[183]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
