{"id":"https://openalex.org/W2121057272","doi":"https://doi.org/10.1109/ivs.2014.6856518","title":"Car detection at night using latent filters","display_name":"Car detection at night using latent filters","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2121057272","doi":"https://doi.org/10.1109/ivs.2014.6856518","mag":"2121057272"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2014.6856518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","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/A5030773349","display_name":"Hossein Tehrani","orcid":"https://orcid.org/0000-0001-5650-5727"},"institutions":[{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hossein Tehrani","raw_affiliation_strings":["Corporate R&D Div.3, DENSO CORPORATION"],"affiliations":[{"raw_affiliation_string":"Corporate R&D Div.3, DENSO CORPORATION","institution_ids":["https://openalex.org/I67530263"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112222770","display_name":"Taiki Kawano","orcid":null},"institutions":[{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Taiki Kawano","raw_affiliation_strings":["DRIVING ASSIST & SAFETY ENG. DIV. 1, DENSO CORPORATION","[DRIVING ASSIST & SAFETY ENG. DIV. 1, DENSO CORPORATION]"],"affiliations":[{"raw_affiliation_string":"DRIVING ASSIST & SAFETY ENG. DIV. 1, DENSO CORPORATION","institution_ids":["https://openalex.org/I67530263"]},{"raw_affiliation_string":"[DRIVING ASSIST & SAFETY ENG. DIV. 1, DENSO CORPORATION]","institution_ids":["https://openalex.org/I67530263"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112282385","display_name":"Seiichi Mita","orcid":null},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Seiichi Mita","raw_affiliation_strings":["Research Center for Smart Vehicles of Toyota Technological Institute the Toyota Technological Institute, Nagoya, 2-12-1 Hisakata Tenpaku-ku, Japan","Research Center for Smart Vehicles of Toyota, Technological Institute the Toyota Technological Institute, Nagoya, 2-12-1 Hisakata Tenpaku-ku, Japan"],"affiliations":[{"raw_affiliation_string":"Research Center for Smart Vehicles of Toyota Technological Institute the Toyota Technological Institute, Nagoya, 2-12-1 Hisakata Tenpaku-ku, Japan","institution_ids":["https://openalex.org/I4840577"]},{"raw_affiliation_string":"Research Center for Smart Vehicles of Toyota, Technological Institute the Toyota Technological Institute, Nagoya, 2-12-1 Hisakata Tenpaku-ku, Japan","institution_ids":["https://openalex.org/I4840577"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030773349"],"corresponding_institution_ids":["https://openalex.org/I67530263"],"apc_list":null,"apc_paid":null,"fwci":0.9755,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.81077817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"10","issue":null,"first_page":"839","last_page":"844"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/visibility","display_name":"Visibility","score":0.826813817024231},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8023231625556946},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6903409957885742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6574125289916992},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6122297644615173},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5771532654762268},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4777368903160095},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4597506821155548},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2210390269756317},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12252268195152283},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08545345067977905},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07464918494224548}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.826813817024231},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8023231625556946},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6903409957885742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6574125289916992},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6122297644615173},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5771532654762268},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4777368903160095},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4597506821155548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2210390269756317},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12252268195152283},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08545345067977905},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07464918494224548},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2014.6856518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856518","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1481552826","https://openalex.org/W1968933322","https://openalex.org/W1982428585","https://openalex.org/W2036989445","https://openalex.org/W2080286758","https://openalex.org/W2105529173","https://openalex.org/W2122146326","https://openalex.org/W2127782573","https://openalex.org/W2139432235","https://openalex.org/W2141617683","https://openalex.org/W2142623206","https://openalex.org/W2149831484","https://openalex.org/W2151693816","https://openalex.org/W2168356304","https://openalex.org/W2186094539","https://openalex.org/W2545226175","https://openalex.org/W2616657226","https://openalex.org/W6680579697"],"related_works":["https://openalex.org/W2392812199","https://openalex.org/W4200176076","https://openalex.org/W598185802","https://openalex.org/W2355516524","https://openalex.org/W2361471170","https://openalex.org/W2025616642","https://openalex.org/W1954972543","https://openalex.org/W2954738200","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Deformable":[0],"part":[1,58],"models":[2],"(DPM)":[3],"already":[4,15],"proved":[5],"great":[6],"performance":[7],"for":[8],"objects":[9,30,55,68],"detection":[10],"and":[11,72,115,131],"many":[12],"extensions":[13],"have":[14,21,88],"published":[16],"in":[17,31,56,61,98,117,135],"literature.":[18],"DPMs":[19],"generally":[20],"high":[22],"performance,":[23],"though":[24],"they":[25],"dramatically":[26],"fail":[27],"to":[28,50,83,92,110,128],"detect":[29,93,129],"challenging":[32,62,107],"environments":[33],"such":[34],"as":[35],"night":[36,96,139],"time.":[37,140],"This":[38],"paper":[39],"proposes":[40],"a":[41,106],"method":[42,91],"based":[43],"on":[44],"the":[45,52,67,77,123,126],"idea":[46],"of":[47,54,66,79,125],"latent":[48,73],"parts":[49,65,74],"optimize":[51,76],"structure":[53,78],"deformable":[57],"models.":[59],"Even":[60],"environment":[63],"some":[64],"are":[69],"still":[70],"visible":[71],"can":[75],"DPM's":[80],"object":[81],"model":[82,127],"catch":[84],"significant":[85],"features.":[86],"We":[87],"evaluated":[89],"proposed":[90],"cars":[94,134],"at":[95,138],"time":[97],"urban":[99,118,136],"area":[100],"using":[101],"IR":[102],"camera.":[103],"It":[104],"is":[105],"problem":[108],"due":[109],"low":[111],"visibility,":[112],"light":[113],"distortion":[114],"illumination/glare":[116],"area.":[119],"Experimental":[120],"results":[121],"prove":[122],"effectiveness":[124],"close":[130],"medium":[132],"range":[133],"scenes":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
