{"id":"https://openalex.org/W4362684581","doi":"https://doi.org/10.2352/ei.2023.35.16.avm-118","title":"Using simulation to quantify the performance of automotive perception systems","display_name":"Using simulation to quantify the performance of automotive perception systems","publication_year":2023,"publication_date":"2023-01-16","ids":{"openalex":"https://openalex.org/W4362684581","doi":"https://doi.org/10.2352/ei.2023.35.16.avm-118"},"language":"en","primary_location":{"id":"doi:10.2352/ei.2023.35.16.avm-118","is_oa":false,"landing_page_url":"http://dx.doi.org/10.2352/ei.2023.35.16.avm-118","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-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/A5040517835","display_name":"Zhenyi Liu","orcid":"https://orcid.org/0000-0001-6550-489X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenyi Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017998146","display_name":"Devesh Shah","orcid":"https://orcid.org/0009-0005-6891-2924"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Devesh Shah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024569249","display_name":"Alireza Rahimpour","orcid":"https://orcid.org/0000-0003-3716-1900"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alireza Rahimpour","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005728773","display_name":"Devesh Upadhyay","orcid":"https://orcid.org/0000-0002-2399-1850"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Devesh Upadhyay","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013356576","display_name":"Joyce Farrell","orcid":"https://orcid.org/0000-0003-3919-1978"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joyce Farrell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074011246","display_name":"Brian A. Wandell","orcid":"https://orcid.org/0000-0002-2974-1836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brian Wandell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.959,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.80207657,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"35","issue":"16","first_page":"118","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11165","display_name":"Image and Video Quality Assessment","score":0.98580002784729,"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/computer-science","display_name":"Computer science","score":0.7510623335838318},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.6146079301834106},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.6116721630096436},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5391817688941956},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5332042574882507},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.46085992455482483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4534561336040497},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44318288564682007},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4420356750488281},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.41523271799087524},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3495813012123108},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3395649194717407},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1381041407585144},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13059663772583008},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.12971311807632446}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7510623335838318},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.6146079301834106},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.6116721630096436},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5391817688941956},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5332042574882507},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.46085992455482483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4534561336040497},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44318288564682007},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4420356750488281},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.41523271799087524},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3495813012123108},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3395649194717407},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1381041407585144},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13059663772583008},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.12971311807632446},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/ei.2023.35.16.avm-118","is_oa":false,"landing_page_url":"http://dx.doi.org/10.2352/ei.2023.35.16.avm-118","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2090093270","https://openalex.org/W4312857205","https://openalex.org/W2309573947","https://openalex.org/W2183878799","https://openalex.org/W2739874619","https://openalex.org/W1604511055","https://openalex.org/W2066730339","https://openalex.org/W4213228110","https://openalex.org/W2607572884","https://openalex.org/W2164918837"],"abstract_inverted_index":{"The":[0,19],"design":[1],"and":[2,80,113,121,141],"evaluation":[3],"of":[4,61,78,87,95],"complex":[5],"systems":[6,63],"can":[7,21],"benefit":[8],"from":[9],"a":[10,16,76,93,116,142],"software":[11,52],"simulation":[12,20,51],"-":[13],"sometimes":[14],"called":[15],"digital":[17],"twin.":[18],"be":[22],"used":[23],"to":[24,29,38,57,136],"characterize":[25],"system":[26,50,107,119],"performance":[27,32,60,108,130],"or":[28],"test":[30],"its":[31],"under":[33,132],"conditions":[34],"that":[35,54,98],"are":[36],"difficult":[37],"measure":[39,84],"(e.g.,":[40],"nighttime":[41,133],"for":[42,64,138],"automotive":[43],"perception":[44],"systems).":[45],"We":[46,68,105,125],"describe":[47,69],"the":[48,59,85,128],"image":[49,62],"tools":[53],"we":[55,91,114],"use":[56],"evaluate":[58],"object":[65,122],"(automobile)":[66],"detection.":[67],"experiments":[70],"with":[71,75],"13":[72],"different":[73,103],"cameras":[74,140],"variety":[77],"optics":[79],"pixel":[81],"sizes.":[82],"To":[83],"impact":[86],"camera":[88],"spatial":[89],"resolution,":[90],"designed":[92],"collection":[94],"driving":[96],"scenes":[97],"had":[99],"cars":[100],"at":[101],"many":[102],"distances.":[104],"quantified":[106,127],"by":[109],"measuring":[110],"average":[111],"precision":[112],"report":[115],"trend":[117],"relating":[118],"resolution":[120],"detection":[123],"performance.":[124],"also":[126],"large":[129],"degradation":[131],"conditions,":[134],"compared":[135],"daytime,":[137],"all":[139],"COCO":[143],"pre-trained":[144],"network.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}