{"id":"https://openalex.org/W4312711729","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936847","title":"Highway Surveillance System Using Deep Learning Artificial Neural Networks","display_name":"Highway Surveillance System Using Deep Learning Artificial Neural Networks","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4312711729","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936847"},"language":"en","primary_location":{"id":"doi:10.1109/iicaiet55139.2022.9936847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936847","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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/A5088887929","display_name":"Pu Chuan-Hsian","orcid":null},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Pu Chuan-Hsian","raw_affiliation_strings":["University of Nottingham Malaysia,Department of Electrical and Electronic Engineering,Semenyih,Malaysia","Department of Electrical and Electronic Engineering, University of Nottingham Malaysia, Semenyih, Malaysia"],"affiliations":[{"raw_affiliation_string":"University of Nottingham Malaysia,Department of Electrical and Electronic Engineering,Semenyih,Malaysia","institution_ids":["https://openalex.org/I155043079"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010997537","display_name":"Chun-Shen Sea","orcid":null},"institutions":[{"id":"https://openalex.org/I155043079","display_name":"University of Nottingham Malaysia Campus","ror":"https://ror.org/04mz9mt17","country_code":"MY","type":"education","lineage":["https://openalex.org/I142263535","https://openalex.org/I155043079"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Chun-Shen Sea","raw_affiliation_strings":["University of Nottingham Malaysia,Department of Electrical and Electronic Engineering,Semenyih,Malaysia","Department of Electrical and Electronic Engineering, University of Nottingham Malaysia, Semenyih, Malaysia"],"affiliations":[{"raw_affiliation_string":"University of Nottingham Malaysia,Department of Electrical and Electronic Engineering,Semenyih,Malaysia","institution_ids":["https://openalex.org/I155043079"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Nottingham Malaysia, Semenyih, Malaysia","institution_ids":["https://openalex.org/I155043079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5088887929"],"corresponding_institution_ids":["https://openalex.org/I155043079"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15129046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962999820709229,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.7930455207824707},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7146887183189392},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.7045339345932007},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6830322742462158},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6620775461196899},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6241310834884644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5531628131866455},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.43847641348838806},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4157809615135193},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13826146721839905},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.07673195004463196},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07539117336273193},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06261759996414185}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7930455207824707},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7146887183189392},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.7045339345932007},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6830322742462158},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6620775461196899},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6241310834884644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5531628131866455},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.43847641348838806},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4157809615135193},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13826146721839905},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.07673195004463196},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07539117336273193},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06261759996414185}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iicaiet55139.2022.9936847","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936847","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1915809311","https://openalex.org/W2098335175","https://openalex.org/W2109708364","https://openalex.org/W2119523866","https://openalex.org/W2152176621","https://openalex.org/W2156828505","https://openalex.org/W3128639919"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,84,116],"novel":[4],"moving":[5,49],"vehicle":[6],"detection":[7],"model":[8],"for":[9],"highway":[10],"surveillance.":[11],"The":[12,29,57,101,125],"models":[13,20],"are":[14,45,112],"developed":[15],"based":[16],"on":[17,41,73],"machine":[18],"learning-based":[19],"by":[21],"leveraging":[22],"the":[23,32,42,52,74],"powerful":[24],"deep":[25],"learning":[26],"neural":[27],"network.":[28],"purpose":[30],"of":[31,70,109],"research":[33],"is":[34],"to":[35,47,93,137],"study":[36],"and":[37,54],"analyze":[38],"drivers'":[39],"behaviours":[40],"road.":[43],"Methods":[44],"proposed":[46],"detect":[48],"vehicles":[50,68,72,111],"using":[51],"Darknet":[53],"TensorFlow":[55],"frameworks.":[56],"results":[58],"show":[59],"that":[60,105],"Tensorflow":[61],"framework":[62,103,127],"could":[63],"barely":[64],"correctly":[65,113],"identify":[66],"three":[67],"out":[69,108],"nine":[71,110],"video":[75],"frame":[76],"with":[77,86,118,130,139],"one":[78,120],"car":[79,117,121],"being":[80,122],"incorrectly":[81],"classified":[82,114],"as":[83,115],"truck":[85],"confident":[87,132],"levels":[88,133],"varying":[89],"widely":[90],"from":[91,135],"19.10%":[92],"92.52%":[94],"inconsistently":[95],"having":[96],"wide":[97],"spreading":[98,141],"in":[99,142],"percentages.":[100,143],"darknet":[102,126],"shows":[104],"all":[106],"eight":[107],"only":[119],"labelled":[123],"incorrectly.":[124],"has":[128],"shown":[129],"improved":[131],"ranging":[134],"46.38%":[136],"77.59%":[138],"lower":[140]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}