{"id":"https://openalex.org/W4226455208","doi":"https://doi.org/10.1109/tits.2022.3180229","title":"DMRVisNet: Deep Multihead Regression Network for Pixel-Wise Visibility Estimation Under Foggy Weather","display_name":"DMRVisNet: Deep Multihead Regression Network for Pixel-Wise Visibility Estimation Under Foggy Weather","publication_year":2022,"publication_date":"2022-06-10","ids":{"openalex":"https://openalex.org/W4226455208","doi":"https://doi.org/10.1109/tits.2022.3180229"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3180229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3180229","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","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/A5068151620","display_name":"You Jing","orcid":"https://orcid.org/0000-0002-3724-7918"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing You","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3724-7918","affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046933572","display_name":"Shaocheng Jia","orcid":"https://orcid.org/0000-0001-9586-5151"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shaocheng Jia","raw_affiliation_strings":["Department of Civil Engineering, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-9586-5151","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636075","display_name":"Xin Pei","orcid":"https://orcid.org/0000-0003-3807-2264"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Pei","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081663090","display_name":"Danya Yao","orcid":"https://orcid.org/0000-0001-5032-6322"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danya Yao","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5032-6322","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.447,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.9034606,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":"11","first_page":"22354","last_page":"22366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","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/T11019","display_name":"Image Enhancement Techniques","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/T10531","display_name":"Advanced Vision and Imaging","score":0.9944000244140625,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9936000108718872,"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":0.9428044557571411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7702834606170654},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7447138428688049},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5764926075935364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49957704544067383},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4618834853172302},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43342751264572144},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3418262004852295},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3318108022212982},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32436662912368774},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12949448823928833},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.12795805931091309}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.9428044557571411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702834606170654},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7447138428688049},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5764926075935364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49957704544067383},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4618834853172302},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43342751264572144},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3418262004852295},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3318108022212982},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32436662912368774},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12949448823928833},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.12795805931091309}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3180229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3180229","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G3583858122","display_name":null,"funder_award_id":"71671100","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8208538107","display_name":null,"funder_award_id":"2021YFC3001500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1496387809","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1879061964","https://openalex.org/W1883599443","https://openalex.org/W1984059906","https://openalex.org/W1989830318","https://openalex.org/W1990592195","https://openalex.org/W2003709967","https://openalex.org/W2013569887","https://openalex.org/W2028990532","https://openalex.org/W2036649100","https://openalex.org/W2056076863","https://openalex.org/W2097900287","https://openalex.org/W2114504777","https://openalex.org/W2116619110","https://openalex.org/W2116845609","https://openalex.org/W2120268610","https://openalex.org/W2133665775","https://openalex.org/W2139750925","https://openalex.org/W2149723649","https://openalex.org/W2163605009","https://openalex.org/W2163996375","https://openalex.org/W2194775991","https://openalex.org/W2256362396","https://openalex.org/W2615547864","https://openalex.org/W2738752875","https://openalex.org/W2748021867","https://openalex.org/W2755659793","https://openalex.org/W2758874168","https://openalex.org/W2767445710","https://openalex.org/W2768780262","https://openalex.org/W2784322219","https://openalex.org/W2792150483","https://openalex.org/W2796917578","https://openalex.org/W2883789162","https://openalex.org/W2920956473","https://openalex.org/W2944926124","https://openalex.org/W2968860216","https://openalex.org/W2985775862","https://openalex.org/W3111640254","https://openalex.org/W3121281282","https://openalex.org/W3128913384","https://openalex.org/W3169864200","https://openalex.org/W3215985143","https://openalex.org/W4295312788","https://openalex.org/W6629462856","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6647720530","https://openalex.org/W6684191040","https://openalex.org/W6750383598","https://openalex.org/W6766978945","https://openalex.org/W6796394224","https://openalex.org/W6804309128"],"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/W4226107239","https://openalex.org/W4280562100"],"abstract_inverted_index":{"Scene":[0],"perception":[1],"is":[2,164,214,221],"essential":[3],"for":[4,153,183],"driving":[5],"decision-making":[6],"and":[7,50,77,99,194],"traffic":[8,48],"safety.":[9,51],"However,":[10],"fog,":[11],"as":[12,135],"a":[13,136,150,177,203],"kind":[14],"of":[15,119,142,161,240],"common":[16],"weather,":[17,185],"frequently":[18],"appears":[19],"in":[20,25,168,211],"the":[21,34,40,66,70,94,100,107,111,115,122,126,133,154,158,189,200,217,232],"real":[22],"world,":[23],"especially":[24],"mountain":[26],"areas,":[27],"making":[28],"it":[29],"difficult":[30],"to":[31,68,92,175,238],"accurately":[32],"observe":[33],"surrounding":[35],"environments.":[36],"Therefore,":[37],"precisely":[38],"estimating":[39],"visibility":[41,71,95,108,123,134,138,144],"under":[42],"foggy":[43,184,209],"weather":[44],"can":[45,173],"significantly":[46],"benefit":[47,174],"management":[49],"To":[52,198],"address":[53],"this,":[54],"most":[55],"current":[56],"methods":[57,74,146],"use":[58],"professional":[59],"instruments":[60],"outfitted":[61],"at":[62,223],"fixed":[63],"locations":[64],"on":[65],"roads":[67],"perform":[69],"measurement;":[72],"these":[73],"are":[75],"expensive":[76],"less":[78],"flexible.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83,131],"propose":[84],"an":[85],"innovative":[86],"end-to-end":[87],"convolutional":[88,127],"neural":[89,128],"network":[90],"framework":[91],"estimate":[93,132],"leveraging":[96],"Koschmieder\u2019s":[97],"law":[98],"image":[101],"data.":[102],"The":[103],"proposed":[104,116,201,233],"method":[105,163,234],"estimates":[106],"by":[109],"integrating":[110],"physical":[112],"model":[113],"into":[114],"framework,":[117,202],"instead":[118],"directly":[120],"predicting":[121],"value":[124,152],"via":[125],"network.":[129],"Moreover,":[130],"pixel-wise":[137],"map":[139],"against":[140],"those":[141,239],"previous":[143],"measurement":[145],"which":[147,172,220],"solely":[148],"predict":[149],"single":[151],"entire":[155],"image.":[156],"Thus,":[157],"estimated":[159],"result":[160],"our":[162],"more":[165,178],"informative,":[166],"particularly":[167],"uneven":[169],"fog":[170],"scenarios,":[171],"developing":[176],"precise":[179],"early":[180],"warning":[181],"system":[182],"thereby":[186],"better":[187],"protecting":[188],"intelligent":[190],"transportation":[191],"infrastructure":[192],"systems":[193],"promoting":[195],"their":[196],"development.":[197],"validate":[199],"virtual":[204],"dataset,":[205],"FACI,":[206],"containing":[207],"3,000":[208],"images":[210],"different":[212],"concentrations,":[213],"collected":[215],"using":[216],"AirSim":[218],"platform,":[219],"available":[222],"<uri":[224],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/coutyou/FoggyAirsimCityImages</uri>":[226],".":[227],"Detailed":[228],"experiments":[229],"show":[230],"that":[231],"achieves":[235],"performance":[236],"competitive":[237],"state-of-the-art":[241],"methods.":[242]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
