{"id":"https://openalex.org/W1580816966","doi":"https://doi.org/10.1109/ijcnn.2003.1223868","title":"A design of the object detection system using the RGA","display_name":"A design of the object detection system using the RGA","publication_year":2003,"publication_date":"2003-01-01","ids":{"openalex":"https://openalex.org/W1580816966","doi":"https://doi.org/10.1109/ijcnn.2003.1223868","mag":"1580816966"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","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/A5067484401","display_name":"Seiki Yoshimori","orcid":null},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"S. Yoshimori","raw_affiliation_strings":["Tokushima Univ., Japan","Tokushima University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokushima Univ., Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Tokushima University, Japan","institution_ids":["https://openalex.org/I922474255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020657583","display_name":"Yasue Mitsukura","orcid":"https://orcid.org/0000-0001-5575-8589"},"institutions":[{"id":"https://openalex.org/I163770644","display_name":"Okayama University","ror":"https://ror.org/02pc6pc55","country_code":"JP","type":"education","lineage":["https://openalex.org/I163770644"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Y. Mitsukura","raw_affiliation_strings":["Okayama University, Okayama, Japan","Okayama University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Okayama University, Okayama, Japan","institution_ids":["https://openalex.org/I163770644"]},{"raw_affiliation_string":"Okayama University","institution_ids":["https://openalex.org/I163770644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113740382","display_name":"Minoru Fukumi","orcid":null},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"M. Fukumi","raw_affiliation_strings":["University of Tokushima, Tokushima, Japan","Tokushima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Tokushima University","institution_ids":["https://openalex.org/I922474255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057874433","display_name":"Norio Akamatsu","orcid":null},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"N. Akamatsu","raw_affiliation_strings":["University of Tokushima, Tokushima, Japan","Tokushima University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"Tokushima University","institution_ids":["https://openalex.org/I922474255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.07808023,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"84","issue":null,"first_page":"1227","last_page":"1231 vol.2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9901999831199646,"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":0.9901999831199646,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.932699978351593,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/brightness","display_name":"Brightness","score":0.6602855324745178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6257975101470947},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5907925963401794},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5881551504135132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5848717093467712},{"id":"https://openalex.org/keywords/license","display_name":"License","score":0.5431458353996277},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5212603211402893},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5178813934326172},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.45148545503616333},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3678539991378784},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.28592970967292786},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.0982837975025177},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07902327179908752},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.0696442723274231}],"concepts":[{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.6602855324745178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6257975101470947},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5907925963401794},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5881551504135132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5848717093467712},{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.5431458353996277},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5212603211402893},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5178813934326172},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.45148545503616333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3678539991378784},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28592970967292786},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0982837975025177},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07902327179908752},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0696442723274231},{"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/ijcnn.2003.1223868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223868","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W657858200","https://openalex.org/W2004205975","https://openalex.org/W2102946263","https://openalex.org/W6651349261"],"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/W3104168426","https://openalex.org/W2356477822","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"License":[0],"plate":[1,75,103],"recognition":[2],"is":[3,6,12,46,149],"very":[4,13,43],"important":[5],"an":[7],"automobile":[8],"society.":[9],"However,":[10],"it":[11],"difficult":[14],"to":[15,29,114,128],"do":[16],"it,":[17],"because":[18],"the":[19,32,36,63,72,84,96,100,130,133],"background":[20],"and":[21,99,107],"body":[22],"color":[23,104],"of":[24,31,38,89,132,147],"cars":[25,39],"are":[26,77,91,110],"sometimes":[27],"similar":[28],"that":[30],"license":[33],"plate.":[34],"Furthermore,":[35],"detection":[37,148],"moving":[40],"at":[41],"a":[42,53],"high":[44],"speed":[45],"difficult.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51,136],"propose":[52],"new":[54],"robust":[55],"thresholds-determination":[56],"method":[57],"in":[58,126],"various":[59,80],"backgrounds":[60],"by":[61,112,118,140],"using":[62,70,119,141],"real":[64,142],"coded":[65],"genetic":[66],"algorithm":[67],"(RGA).":[68],"By":[69],"RGA,":[71],"most":[73,101],"likely":[74,102],"colors":[76],"decided":[78],"under":[79],"light":[81],"conditions.":[82],"First,":[83],"average":[85],"brightness":[86],"Y":[87,97],"values":[88],"images":[90],"calculated.":[92],"Next,":[93],"relationship":[94],"between":[95],"value":[98],"thresholds":[105],"(upper":[106],"lower":[108],"bounds)":[109],"obtained":[111],"GA":[113],"estimate":[115],"threshold":[116],"equations":[117],"recursive":[120],"least":[121],"squares":[122],"(RLS)":[123],"algorithm.":[124],"Finally,":[125],"order":[127],"show":[129,137],"effectiveness":[131],"proposed":[134],"method,":[135],"simulation":[138],"examples":[139],"images.":[143],"The":[144],"resulting":[145],"rate":[146],"85.0%.":[150]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}