{"id":"https://openalex.org/W2754536314","doi":"https://doi.org/10.1109/icip.2017.8296912","title":"Convolutional neural networks for license plate detection in images","display_name":"Convolutional neural networks for license plate detection in images","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2754536314","doi":"https://doi.org/10.1109/icip.2017.8296912","mag":"2754536314"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5049379400","display_name":"Francisco Delmar Kurpiel","orcid":null},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Francisco Delmar Kurpiel","raw_affiliation_strings":["Federal University of Technology, Parana, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Technology, Parana, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055631823","display_name":"Rodrigo Minetto","orcid":"https://orcid.org/0000-0003-2277-4632"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rodrigo Minetto","raw_affiliation_strings":["Federal University of Technology, Parana, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Technology, Parana, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001239191","display_name":"Bogdan Tomoyuki Nassu","orcid":"https://orcid.org/0000-0001-6441-8543"},"institutions":[{"id":"https://openalex.org/I1283613182","display_name":"Universidade Tecnol\u00f3gica Federal do Paran\u00e1","ror":"https://ror.org/002v2kq79","country_code":"BR","type":"education","lineage":["https://openalex.org/I1283613182"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Bogdan Tomoyuki Nassu","raw_affiliation_strings":["Federal University of Technology, Parana, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Technology, Parana, Brazil","institution_ids":["https://openalex.org/I1283613182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049379400"],"corresponding_institution_ids":["https://openalex.org/I1283613182"],"apc_list":null,"apc_paid":null,"fwci":5.6502,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.96332046,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3395","last_page":"3399"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":1.0,"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":1.0,"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":0.9961000084877014,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9807999730110168,"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/license","display_name":"License","score":0.8262077569961548},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7858639359474182},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7858401536941528},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7692681550979614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7547280788421631},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7349399924278259},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5523914098739624},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5090045928955078},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4851401746273041},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47029563784599304},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44070714712142944},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.42989373207092285},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.41665083169937134},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08784133195877075},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07277709245681763},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05968201160430908}],"concepts":[{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.8262077569961548},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7858639359474182},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7858401536941528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7692681550979614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7547280788421631},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7349399924278259},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5523914098739624},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5090045928955078},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4851401746273041},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47029563784599304},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44070714712142944},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.42989373207092285},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.41665083169937134},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08784133195877075},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07277709245681763},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05968201160430908},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8296912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296912","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1972193443","https://openalex.org/W1975399404","https://openalex.org/W1994871538","https://openalex.org/W1995026832","https://openalex.org/W1997245199","https://openalex.org/W2001297828","https://openalex.org/W2019019933","https://openalex.org/W2031489346","https://openalex.org/W2066019761","https://openalex.org/W2095565388","https://openalex.org/W2097117768","https://openalex.org/W2102608210","https://openalex.org/W2108463990","https://openalex.org/W2112738128","https://openalex.org/W2117539524","https://openalex.org/W2120636275","https://openalex.org/W2135231474","https://openalex.org/W2135449683","https://openalex.org/W2147800946","https://openalex.org/W2160977939","https://openalex.org/W2194775991","https://openalex.org/W2288122362","https://openalex.org/W2524986418","https://openalex.org/W2919115771"],"related_works":["https://openalex.org/W2606446052","https://openalex.org/W2036021480","https://openalex.org/W3195777957","https://openalex.org/W2382668227","https://openalex.org/W2348482143","https://openalex.org/W2024584030","https://openalex.org/W1603675680","https://openalex.org/W4312856422","https://openalex.org/W2969228573","https://openalex.org/W4382050342"],"abstract_inverted_index":{"License":[0],"plate":[1],"detection":[2],"is":[3],"a":[4,16,35,41,45,75,94,103,107],"challenging":[5,76],"task":[6],"when":[7],"dealing":[8],"with":[9],"open":[10],"environments":[11],"and":[12,98],"images":[13],"captured":[14,85],"from":[15,67],"certain":[17],"distance":[18],"by":[19,62],"low-cost":[20],"cameras.":[21],"In":[22],"this":[23],"paper,":[24],"we":[25],"propose":[26],"an":[27],"approach":[28,92],"for":[29,47],"detecting":[30],"license":[31,60,80],"plates":[32,61,81],"based":[33],"on":[34,74,116],"convolutional":[36],"neural":[37],"network":[38],"which":[39],"models":[40],"function":[42],"that":[43,111],"produces":[44],"score":[46],"each":[48],"image":[49],"sub-region,":[50],"allowing":[51],"us":[52],"to":[53],"estimate":[54],"the":[55,58,64,112],"locations":[56],"of":[57,96,100,122],"detected":[59],"combining":[63],"results":[65],"obtained":[66],"sparse":[68],"overlapping":[69],"regions.":[70],"Experiments":[71],"were":[72,114],"performed":[73,115],"benchmark,":[77],"containing":[78],"4,070":[79],"in":[82],"1,829":[83],"images,":[84,118],"under":[86],"several":[87],"weather":[88],"conditions.":[89],"The":[90],"proposed":[91],"achieved":[93],"precision":[95],"0.87":[97],"recall":[99],"0.83,":[101],"outperforming":[102],"state-of-the-art":[104],"detector":[105],"-":[106],"promising":[108],"result,":[109],"given":[110],"experiments":[113],"single":[117],"without":[119],"any":[120],"kind":[121],"preprocessing":[123],"or":[124],"temporal":[125],"integration.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}