{"id":"https://openalex.org/W4213213136","doi":"https://doi.org/10.1145/3489088.3489111","title":"Combining CNN Deep Learning and SVM for Vehicle Classification","display_name":"Combining CNN Deep Learning and SVM for Vehicle Classification","publication_year":2021,"publication_date":"2021-10-05","ids":{"openalex":"https://openalex.org/W4213213136","doi":"https://doi.org/10.1145/3489088.3489111"},"language":"en","primary_location":{"id":"doi:10.1145/3489088.3489111","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489088.3489111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Computer, Control, Informatics and Its Applications","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088578178","display_name":"Uus Khusni","orcid":null},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Uus Khusni","raw_affiliation_strings":["National Research and Inovation Agency, Indonesia and University of Indonesia, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Research and Inovation Agency, Indonesia and University of Indonesia, Indonesia","institution_ids":["https://openalex.org/I29617571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005352277","display_name":"Asep Insani","orcid":"https://orcid.org/0000-0002-3761-5450"},"institutions":[{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]},{"id":"https://openalex.org/I4387154144","display_name":"National Research and Innovation Agency","ror":"https://ror.org/02hmjzt55","country_code":"ID","type":"government","lineage":["https://openalex.org/I4387154144"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Asep Insani","raw_affiliation_strings":["Universitas Indonesia, Indonesia and National Research and Inovation Agency, Indonesia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Indonesia, Indonesia and National Research and Inovation Agency, Indonesia","institution_ids":["https://openalex.org/I29617571","https://openalex.org/I4387154144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7251,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71791703,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12707","display_name":"Vehicle License Plate Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9922000169754028,"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/T13674","display_name":"Computer Science and Engineering","score":0.9696000218391418,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8297007083892822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7348840236663818},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7079594731330872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7071278691291809},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6851209402084351},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.6318767070770264},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5926560163497925},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.5774385929107666},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.49880075454711914},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4750245213508606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4630205035209656},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.4552941620349884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4449656009674072},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4275967478752136},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2179338037967682},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09744781255722046},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.09532797336578369}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8297007083892822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7348840236663818},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7079594731330872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7071278691291809},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6851209402084351},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.6318767070770264},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5926560163497925},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.5774385929107666},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.49880075454711914},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4750245213508606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4630205035209656},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.4552941620349884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4449656009674072},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4275967478752136},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2179338037967682},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09744781255722046},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.09532797336578369},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3489088.3489111","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3489088.3489111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Computer, Control, Informatics and Its Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W3014719091","https://openalex.org/W3045576536","https://openalex.org/W3083485545","https://openalex.org/W3087930840","https://openalex.org/W3094713880","https://openalex.org/W3114952133","https://openalex.org/W3115234192","https://openalex.org/W3115773619","https://openalex.org/W3123728447","https://openalex.org/W3152976204","https://openalex.org/W3157095620","https://openalex.org/W3162472108","https://openalex.org/W3162709871","https://openalex.org/W3179533995"],"related_works":["https://openalex.org/W2986507176","https://openalex.org/W4225852842","https://openalex.org/W3136979370","https://openalex.org/W2995914718","https://openalex.org/W3193301557","https://openalex.org/W3011074480","https://openalex.org/W4311773132","https://openalex.org/W3156786002","https://openalex.org/W2732542196","https://openalex.org/W564581980"],"abstract_inverted_index":{"Vehicle":[0],"classification":[1,40],"plays":[2],"an":[3,7],"important":[4],"role":[5],"in":[6,15,28,44,72,85,128,171],"intelligent":[8],"transportation":[9],"system.":[10],"The":[11,55,79,125,157,168,202],"development":[12],"of":[13,57,75,81,101,137,182],"research":[14,26,130,173],"image":[16],"processing,":[17],"pattern":[18],"recognition,":[19],"and":[20,53,94,123,166,185,200,216],"deep":[21,32,105,158],"learning":[22,33,106,159],"has":[23],"encouraged":[24],"more":[25],"interest":[27],"categorizing":[29],"vehicles":[30],"using":[31,104],"technology.":[34],"In":[35,96],"everyday":[36],"life,":[37],"Automatic":[38],"vehicle":[39,45,58,62,103,187],"can":[41,108,113],"be":[42,109,114],"found":[43],"search,":[46],"real-time":[47],"traffic":[48],"monitoring,":[49],"automatic":[50,99],"toll":[51],"gates,":[52],"others.":[54],"use":[56,80,133],"classifications":[59],"as":[60,142,151],"a":[61,69,82,102,134,143,152],"search":[63],"problem":[64],"is":[65,88,131,162,174,205],"commonly":[66],"used":[67,127,161,170],"by":[68],"police":[70],"officer":[71],"the":[73,175],"case":[74],"car":[76],"robbery":[77],"crimes.":[78],"human":[83],"expert,":[84],"this":[86,97,129,172],"case,":[87,98],"completely":[89],"accurate":[90],"but":[91],"requires":[92],"time":[93],"money.":[95],"categorization":[100],"technology":[107],"one":[110],"solution.":[111],"Vehicles":[112],"categorized":[115],"into":[116],"four":[117,192],"categories:":[118],"Minivans,":[119],"Pickup":[120,197],"Trucks,":[121],"Sedans,":[122],"SUV.":[124],"method":[126,136],"to":[132,154],"combination":[135],"Convolution":[138],"Neural":[139],"Networks":[140],"(CNN)":[141],"feature":[144],"extractor":[145],"with":[146],"Support":[147],"Vector":[148],"Machine":[149],"(SVM)":[150],"classifier":[153],"increase":[155],"accuracy.":[156],"architecture":[160],"CNN":[163],"(AlexNet,":[164],"VGG16,":[165],"Resnet50).":[167],"dataset":[169],"AI":[176],"Standford":[177],"Car":[178],"Dataset":[179],"which":[180],"consists":[181],"16,185":[183],"images":[184],"196":[186,190],"classes.":[188],"From":[189],"classes,":[191],"classes":[193],"were":[194],"selected":[195],"(Minivan,":[196],"Truck,":[198],"Sedan,":[199],"SUV).":[201],"accuracy":[203],"obtained":[204],"AlexNet":[206],"+":[207,212,218],"SVM":[208,213,219],"38.50":[209],"%,":[210],"VGG16":[211],"82.93":[214],"%":[215],"ResNet50":[217],"90.87":[220],"%.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
