{"id":"https://openalex.org/W2896112403","doi":"https://doi.org/10.1109/ivs.2018.8500659","title":"Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving","display_name":"Benchmarking Image Sensors Under Adverse Weather Conditions for Autonomous Driving","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2896112403","doi":"https://doi.org/10.1109/ivs.2018.8500659","mag":"2896112403"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2018.8500659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1912.03238","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mario Bijelic","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mario Bijelic","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tobias Gruber","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Gruber","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":null,"display_name":"Werner Ritter","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Werner Ritter","raw_affiliation_strings":["Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Wilhelm-Runge-Str. 11, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I891521709"],"apc_list":null,"apc_paid":null,"fwci":2.425,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.9378024,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1773","last_page":"1779"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9997000098228455,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9994000196456909,"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":0.9980999827384949,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7556999921798706},{"id":"https://openalex.org/keywords/adverse-weather","display_name":"Adverse weather","score":0.695900022983551},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6333000063896179},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.5099999904632568},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3953000009059906}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7556999921798706},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.695900022983551},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6333000063896179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5672000050544739},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.5099999904632568},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4350999891757965},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3894999921321869},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3587999939918518},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.34880000352859497},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2628999948501587},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.26269999146461487},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ivs.2018.8500659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1912.03238","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03238","pdf_url":"https://arxiv.org/pdf/1912.03238","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1912.03238","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1912.03238","pdf_url":"https://arxiv.org/pdf/1912.03238","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1973444879","https://openalex.org/W1983976362","https://openalex.org/W1995875735","https://openalex.org/W2008835329","https://openalex.org/W2031920744","https://openalex.org/W2098985238","https://openalex.org/W2110644821","https://openalex.org/W2121880036","https://openalex.org/W2123996346","https://openalex.org/W2132476535","https://openalex.org/W2165446961","https://openalex.org/W2402743082","https://openalex.org/W2473494467","https://openalex.org/W2501428645","https://openalex.org/W2563763605","https://openalex.org/W4241600324","https://openalex.org/W6771174174"],"related_works":[],"abstract_inverted_index":{"Adverse":[0],"weather":[1,35,45],"conditions":[2,36],"are":[3,37],"very":[4],"challenging":[5],"for":[6,39,46],"autonomous":[7],"driving":[8],"because":[9],"most":[10],"of":[11,43],"the":[12,41],"state-of-the-art":[13,68,90],"sensors":[14,26,32],"stop":[15],"working":[16],"reliably":[17],"under":[18,80],"these":[19],"conditions.":[20,82],"In":[21],"order":[22],"to":[23,59,67,77,95],"develop":[24],"robust":[25],"and":[27,54,64],"algorithms,":[28],"tests":[29],"with":[30],"current":[31],"in":[33],"defined":[34],"crucial":[38],"determining":[40],"impact":[42],"bad":[44],"each":[47],"sensor.":[48],"This":[49],"work":[50],"describes":[51],"a":[52],"testing":[53],"evaluation":[55],"methodology":[56],"that":[57,86],"helps":[58],"benchmark":[60],"novel":[61],"sensor":[62],"technologies":[63],"compare":[65],"them":[66],"sensors.":[69],"As":[70],"an":[71],"example,":[72],"gated":[73,87],"imaging":[74,79,88,93],"is":[75,84],"compared":[76],"standard":[78,91],"foggy":[81],"It":[83],"shown":[85],"outperforms":[89],"passive":[92],"due":[94],"time-synchronized":[96],"active":[97],"illumination.":[98]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2018-10-26T00:00:00"}
