{"id":"https://openalex.org/W2971492022","doi":"https://doi.org/10.1109/ccoms.2019.8821689","title":"Vehicle Classification with Deep Learning","display_name":"Vehicle Classification with Deep Learning","publication_year":2019,"publication_date":"2019-02-01","ids":{"openalex":"https://openalex.org/W2971492022","doi":"https://doi.org/10.1109/ccoms.2019.8821689","mag":"2971492022"},"language":"en","primary_location":{"id":"doi:10.1109/ccoms.2019.8821689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccoms.2019.8821689","pdf_url":null,"source":{"id":"https://openalex.org/S4306498485","display_name":"2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS)","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":"2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS)","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/A5007018801","display_name":"Watcharin Maungmai","orcid":null},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Watcharin Maungmai","raw_affiliation_strings":["International College, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, Thailand","International College, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"International College, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]},{"raw_affiliation_string":"International College, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008553646","display_name":"Chaiwat Nuthong","orcid":null},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Chaiwat Nuthong","raw_affiliation_strings":["International College, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, Thailand","International College, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"International College, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]},{"raw_affiliation_string":"International College, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand","institution_ids":["https://openalex.org/I91538806"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007018801"],"corresponding_institution_ids":["https://openalex.org/I91538806"],"apc_list":null,"apc_paid":null,"fwci":7.4951,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.97789337,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"294","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9986000061035156,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7922453880310059},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7643093466758728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7441782355308533},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.6454190015792847},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5829420685768127},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5512380599975586},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5376623272895813},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4839230179786682},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4731898307800293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47217386960983276},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4349614083766937},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4245026111602783},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37870633602142334},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3694768249988556},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19564807415008545},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.1646120250225067}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7922453880310059},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7643093466758728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7441782355308533},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.6454190015792847},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5829420685768127},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5512380599975586},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5376623272895813},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4839230179786682},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4731898307800293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47217386960983276},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4349614083766937},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4245026111602783},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37870633602142334},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3694768249988556},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19564807415008545},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.1646120250225067},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccoms.2019.8821689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccoms.2019.8821689","pdf_url":null,"source":{"id":"https://openalex.org/S4306498485","display_name":"2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS)","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":"2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7200000286102295,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1612060419","https://openalex.org/W1869000332","https://openalex.org/W1988115271","https://openalex.org/W1990653740","https://openalex.org/W2046660943","https://openalex.org/W2082047875","https://openalex.org/W2097117768","https://openalex.org/W2137401668","https://openalex.org/W2163605009","https://openalex.org/W2169915211","https://openalex.org/W2218535067","https://openalex.org/W2268423311","https://openalex.org/W2767747911","https://openalex.org/W2963037989","https://openalex.org/W2963552569","https://openalex.org/W3097096317","https://openalex.org/W6628973269","https://openalex.org/W6639204050","https://openalex.org/W6684191040","https://openalex.org/W6684955264"],"related_works":["https://openalex.org/W2766604260","https://openalex.org/W2986507176","https://openalex.org/W3160711233","https://openalex.org/W3011074480","https://openalex.org/W4220996320","https://openalex.org/W3018421652","https://openalex.org/W4281616679","https://openalex.org/W2996856019","https://openalex.org/W2470368200","https://openalex.org/W2912288872"],"abstract_inverted_index":{"Nowadays,":[0],"there":[1,96,167],"are":[2,8,97,168],"many":[3],"traffic":[4,32],"surveillance":[5,20],"systems":[6],"which":[7,102,137],"installed":[9],"in":[10,51,60,139,151,206],"almost":[11],"every":[12],"city":[13],"to":[14,64,80,83,106,192],"record":[15],"events":[16],"and":[17,30,78,174],"traffic.":[18],"The":[19,146,196],"system":[21,40],"is":[22,73,76,93,124,131,138,148,188],"used":[23,43,190],"for":[24,86],"various":[25],"objectives,":[26],"e.g.":[27,109],"vehicles":[28],"searching":[29,37],"real-time":[31],"monitoring,":[33],"etc.":[34,119],"For":[35],"the":[36,39,54,58,68,140,143,156,163],"purpose,":[38],"can":[41,103,202],"be":[42,104],"by":[44],"policeman":[45],"such":[46,128],"as":[47,191],"outlaw's":[48],"vehicle":[49,59,165,170,194],"identification":[50],"crime.":[52],"Typically,":[53],"officers":[55],"manually":[56],"identify":[57],"recorded":[61],"video":[62],"according":[63],"its":[65,160],"appearances.":[66],"Although":[67],"accuracy":[69],"of":[70,127,134,142,159,178,184],"this":[71],"approach":[72],"good,":[74],"it":[75],"time-consuming":[77],"inclined":[79],"faults":[81],"due":[82],"human":[84],"fatigue":[85],"long":[87],"duration":[88],"videos.":[89],"Moreover,":[90],"hiring":[91],"employees":[92],"costly.":[94],"Recently,":[95],"several":[98],"machine":[99],"learning":[100],"methods":[101],"applied":[105],"classify":[107,193],"vehicles,":[108],"Fuzzy":[110],"Logic,":[111],"Decision":[112],"Tree,":[113],"Adaboost,":[114],"Random":[115],"Forest,":[116],"Neural":[117,121],"Network,":[118],"Convolutional":[120],"Network":[122],"(CNN)":[123],"also":[125],"one":[126],"methods.":[129],"CNN":[130,187,201],"a":[132],"type":[133],"Deep":[135],"Learning":[136],"category":[141],"neural":[144],"network.":[145],"method":[147],"very":[149],"well-known":[150],"image":[152],"recognition":[153],"field":[154],"at":[155],"present":[157],"because":[158],"performance.":[161],"In":[162],"proposed":[164],"classification,":[166],"two":[169],"characteristics,":[171],"i.e.":[172],"types":[173],"colors.":[175],"Types":[176],"consist":[177,183],"four":[179],"classes":[180],"while":[181],"colors":[182],"seven":[185],"classes.":[186],"then":[189],"images.":[195],"experimental":[197],"results":[198],"show":[199],"that":[200],"achieve":[203],"high":[204],"performance":[205],"real-world":[207],"applications.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}