{"id":"https://openalex.org/W3113993207","doi":"https://doi.org/10.1109/gcce50665.2020.9291922","title":"Visibility Level Estimation in Winter CCTV Images Based on Decision Level Fusion Using Logistic Regression","display_name":"Visibility Level Estimation in Winter CCTV Images Based on Decision Level Fusion Using Logistic Regression","publication_year":2020,"publication_date":"2020-10-13","ids":{"openalex":"https://openalex.org/W3113993207","doi":"https://doi.org/10.1109/gcce50665.2020.9291922","mag":"3113993207"},"language":"en","primary_location":{"id":"doi:10.1109/gcce50665.2020.9291922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"},"type":"conference-paper","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":false,"raw_author_name":"Shotaro Kawata","raw_affiliation_strings":["Graduate School of Engineering, Hokkaido University N-13, W-8, Kita-ku, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Hokkaido University N-13, W-8, Kita-ku, Sapporo, Hokkaido, 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 N-13, W-8, Kita-ku, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University N-13, W-8, Kita-ku, Sapporo, Hokkaido, 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 N-13, W-8, Kita-ku, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University N-13, W-8, Kita-ku, Sapporo, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"640","last_page":"641"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9980999827384949,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9980999827384949,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.996999979019165,"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":0.8877769112586975},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7866090536117554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.761236310005188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7020142078399658},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6510491967201233},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5889484882354736},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5372016429901123},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5268070697784424},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5083779692649841},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4641472101211548},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4602007567882538},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3714839518070221},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12177059054374695}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.8877769112586975},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7866090536117554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.761236310005188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7020142078399658},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6510491967201233},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5889484882354736},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5372016429901123},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5268070697784424},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5083779692649841},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4641472101211548},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4602007567882538},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3714839518070221},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12177059054374695},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce50665.2020.9291922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 9th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2010135967","https://openalex.org/W2119821739","https://openalex.org/W2144363690","https://openalex.org/W2156520753","https://openalex.org/W2183341477","https://openalex.org/W3109012741","https://openalex.org/W4239510810","https://openalex.org/W6681267187"],"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":{"This":[0],"paper":[1],"proposes":[2],"a":[3],"method":[4,30,86,103],"for":[5],"estimating":[6],"the":[7,33,44,53,56,72,80,84,88],"degree":[8],"of":[9,35,74,79,101],"visibility":[10,61,89],"(visibility":[11],"level)":[12],"in":[13],"winter":[14],"closed-circuit":[15],"television":[16],"(CCTV)":[17],"images":[18,75],"by":[19,47,95,108],"decision":[20],"level":[21],"fusion":[22],"based":[23,64,90],"on":[24,32,65,91],"logistic":[25],"regression":[26],"(LR).":[27],"The":[28,99],"proposed":[29,54,85],"classifies":[31],"basis":[34],"two":[36],"support":[37],"vector":[38],"machines":[39],"(SVMs)":[40],"classifiers":[41],"and":[42,76],"fuses":[43],"classification":[45],"results":[46],"utilizing":[48,109],"LRbased":[49],"late":[50],"fusion.":[51],"In":[52],"method,":[55],"SVMs":[57],"which":[58],"tentatively":[59],"estimate":[60],"are":[62],"constructed":[63],"each":[66],"CCTV":[67,111],"image":[68],"feature":[69],"that":[70],"represents":[71],"contrast":[73],"neuron":[77],"values":[78],"neural":[81],"network.":[82],"Also,":[83],"evaluates":[87],"LR":[92],"model":[93],"trained":[94],"using":[96],"SVM":[97],"outputs.":[98],"effectiveness":[100],"our":[102],"is":[104],"verified":[105],"from":[106],"experiments":[107],"actual":[110],"images.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-26T07:53:14.480251","created_date":"2025-10-10T00:00:00"}