{"id":"https://openalex.org/W1998697499","doi":null,"title":"Car Detection Based on Multi-Cues Integration","display_name":"Car Detection Based on Multi-Cues Integration","publication_year":2008,"publication_date":"2008-02-07","ids":{"openalex":"https://openalex.org/W1998697499","mag":"1998697499"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.80.1399","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.1399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://navi.cs.kumamoto-u.ac.jp/english/publications/pdf/int_thesis/2004-06.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5101867605","display_name":"Zhenfeng Zhu","orcid":"https://orcid.org/0000-0001-7315-3276","observed_orcids":["https://orcid.org/0000-0001-7315-3276"]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenfeng Zhu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Science China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Science China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102146587","display_name":"Hanqing Lu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqing Lu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Science China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Science China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}]},{"author_position":"middle","author":{"id":null,"display_name":"James Hu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"James Hu","raw_affiliation_strings":["Kumamoto University, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kumamoto University, Japan#TAB#","institution_ids":["https://openalex.org/I96036126"]}]},{"author_position":"last","author":{"id":null,"display_name":"Keiichi Uchimura","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I96036126","display_name":"Kumamoto University","ror":"https://ror.org/02cgss904","country_code":"JP","type":"education","lineage":["https://openalex.org/I96036126"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichi Uchimura","raw_affiliation_strings":["Kumamoto University, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kumamoto University, Japan#TAB#","institution_ids":["https://openalex.org/I96036126"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0603,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.93223455,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.5615000128746033,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.5615000128746033,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.16599999368190765,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1298999935388565,"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/car-detection","display_name":"car detection","score":0.9819999933242798},{"id":"https://openalex.org/keywords/outdoor-images","display_name":"outdoor images","score":0.8180000185966492},{"id":"https://openalex.org/keywords/edge-cues","display_name":"edge cues","score":0.6610000133514404},{"id":"https://openalex.org/keywords/interest-points","display_name":"interest points","score":0.984000027179718},{"id":"https://openalex.org/keywords/local-texture","display_name":"local texture","score":0.7400000095367432},{"id":"https://openalex.org/keywords/global-structure","display_name":"global structure","score":0.6919999718666077},{"id":"https://openalex.org/keywords/object-classification","display_name":"object classification","score":0.4090000092983246}],"concepts":[{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.7242958545684814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6936158537864685},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6520506143569946},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6316127181053162},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6157180666923523},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5202071070671082},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4797609746456146},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4791002571582794},{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.4471113681793213},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18839862942695618},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.80.1399","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.1399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://navi.cs.kumamoto-u.ac.jp/english/publications/pdf/int_thesis/2004-06.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1608462934","https://openalex.org/W1840030010","https://openalex.org/W1914401667","https://openalex.org/W1949116567","https://openalex.org/W1996550590","https://openalex.org/W2094590153","https://openalex.org/W2095757522","https://openalex.org/W2111308925","https://openalex.org/W2120210190","https://openalex.org/W2155511848","https://openalex.org/W2160225842","https://openalex.org/W2160754664","https://openalex.org/W2163814366","https://openalex.org/W2164598857"],"related_works":["https://openalex.org/W2102883642","https://openalex.org/W839863090","https://openalex.org/W2598466753","https://openalex.org/W7096671838","https://openalex.org/W2275523940","https://openalex.org/W2002100576","https://openalex.org/W2120916774","https://openalex.org/W3108654786","https://openalex.org/W2162131940","https://openalex.org/W2065557289"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"present":[4],"a":[5,101,131],"novel":[6,22],"fast":[7],"multi-cues":[8],"based":[9,25,90],"car":[10,53,126],"detection":[11,133],"technique":[12],"in":[13,123],"still":[14],"outdoor":[15],"images.":[16],"On":[17,55],"the":[18,42,46,52,56,71,75,110],"bottom":[19],"level,":[20,58],"two":[21],"area":[23,97],"templates":[24],"on":[26],"edge":[27],"cue":[28,32,62,66],"and":[29,63,81,116,127,130],"interest":[30],"points":[31],"are":[33,67,79],"first":[34],"designed,":[35],"which":[36],"can":[37],"rapidly":[38],"reject":[39],"most":[40],"of":[41,48,51,112],"non-car":[43,128],"sub-windows":[44],"at":[45],"cost":[47],"missing":[49],"few":[50],"sub-windows.":[54],"top":[57],"both":[59],"global":[60,72,113],"structure":[61,73,114],"local":[64,91,117],"texture":[65,92,118],"considered.":[68],"To":[69],"character":[70],"property":[74,93,115,119],"odd":[76],"Gabor":[77,89],"moments":[78],"introduced":[80],"trained":[82],"by":[83],"SVMs.":[84],"The":[85,104],"multi":[86],"channels":[87],"even":[88],"extracted":[94],"from":[95],"corner":[96],"is":[98,120,137],"modeled":[99],"as":[100],"Gaussian":[102],"distribution.":[103],"final":[105],"experiment":[106],"results":[107],"show":[108],"that":[109],"integration":[111],"more":[121],"powerful":[122],"discrimination":[124],"between":[125],"objects":[129],"high":[132],"accurate":[134],"93":[135],"%":[136],"obtained.":[138],"1.":[139]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-09-29T14:09:16.559479","created_date":"2016-06-24T00:00:00"}
