{"id":"https://openalex.org/W3109012741","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258122","title":"An Estimation Method of Visibility Level on Winter Road Based on Multiple Features in CCTV Images","display_name":"An Estimation Method of Visibility Level on Winter Road Based on Multiple Features in CCTV Images","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3109012741","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258122","mag":"3109012741"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan49838.2020.9258122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5033085363","display_name":"Shotaro Kawata","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shotaro Kawata","raw_affiliation_strings":["Graduate School of Engineering, Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073197671","display_name":"Sho Takahashi","orcid":"https://orcid.org/0000-0002-5338-5990"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sho Takahashi","raw_affiliation_strings":["Faculty of Engineering, Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113963450","display_name":"Toru Hagiwara","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toru Hagiwara","raw_affiliation_strings":["Faculty of Engineering, Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033085363"],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":0.1954,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51270417,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980000257492065,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9980000257492065,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9921000003814697,"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":0.9593477249145508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099555730819702},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.704571008682251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6929727792739868},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5950630903244019},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5949174165725708},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5642651915550232},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48471951484680176},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45080795884132385},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44267627596855164},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4396373927593231},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.413627952337265},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14089137315750122},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1192401647567749}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.9593477249145508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099555730819702},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.704571008682251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6929727792739868},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5950630903244019},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5949174165725708},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5642651915550232},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48471951484680176},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45080795884132385},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44267627596855164},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4396373927593231},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.413627952337265},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14089137315750122},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1192401647567749},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan49838.2020.9258122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2088245379","https://openalex.org/W2119821739","https://openalex.org/W2183341477","https://openalex.org/W2799043583","https://openalex.org/W2983723229","https://openalex.org/W4239510810","https://openalex.org/W4249838020"],"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/W4220843223","https://openalex.org/W4226107239"],"abstract_inverted_index":{"Since":[0],"drivers":[1],"acquire":[2],"a":[3,31,92],"lot":[4],"of":[5,11,14,54,83,94,98,113],"information":[6],"with":[7],"eyes,":[8],"the":[9,12,19,35,39,48,51,81,84,95,100,104,111,114],"estimation":[10],"level":[13,37,53,86,106],"visibility":[15,36,52,85,105],"(visibility":[16],"level)":[17],"on":[18,38,60,91],"winter":[20,40],"roads":[21,41],"contributes":[22],"toward":[23],"enhancing":[24],"traffic":[25],"safety.":[26],"Therefore,":[27],"this":[28],"paper":[29],"proposes":[30],"method":[32,102],"for":[33,78],"estimating":[34],"from":[42],"closed-circuit":[43],"television":[44],"(CCTV)":[45],"images.":[46],"In":[47],"proposed":[49,101,115],"method,":[50],"each":[55,79],"image":[56],"is":[57],"estimated":[58],"based":[59,90],"features":[61],"acquired":[62],"via":[63],"Fourier":[64],"transform":[65],"and":[66],"Convolutional":[67],"Neural":[68],"Network":[69],"(CNN).":[70],"Specifically,":[71],"by":[72],"constructing":[73],"support":[74],"vector":[75],"machines":[76],"(SVMs)":[77],"feature,":[80],"probabilities":[82,97],"are":[87],"calculated.":[88],"Furthermore,":[89],"comparison":[93],"calculated":[96],"SVMs,":[99],"estimates":[103],"accurately.":[107],"Experimental":[108],"results":[109],"show":[110],"effectiveness":[112],"method.":[116]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}