{"id":"https://openalex.org/W3116460115","doi":"https://doi.org/10.1109/gcce50665.2020.9291862","title":"An Estimation Method of Visibility Level Based on Low Rank Matrix Completion Using Positional Relationship of GPV Data","display_name":"An Estimation Method of Visibility Level Based on Low Rank Matrix Completion Using Positional Relationship of GPV Data","publication_year":2020,"publication_date":"2020-10-13","ids":{"openalex":"https://openalex.org/W3116460115","doi":"https://doi.org/10.1109/gcce50665.2020.9291862","mag":"3116460115"},"language":"en","primary_location":{"id":"doi:10.1109/gcce50665.2020.9291862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291862","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/A5009564531","display_name":"Gen Ohkama","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":"Gen Ohkama","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":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"638","last_page":"639"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9656999707221985,"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":0.9627000093460083,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.9552088379859924},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6543067097663879},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.6291629076004028},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.5365614295005798},{"id":"https://openalex.org/keywords/safer","display_name":"SAFER","score":0.5191737413406372},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"Low-rank approximation","score":0.5063928365707397},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.5050082802772522},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4903557300567627},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.461032897233963},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.43543022871017456},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.41732877492904663},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4110843241214752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3451891243457794},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3336334228515625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22990307211875916},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19636783003807068},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11659941077232361}],"concepts":[{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.9552088379859924},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6543067097663879},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.6291629076004028},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.5365614295005798},{"id":"https://openalex.org/C2776654903","wikidata":"https://www.wikidata.org/wiki/Q2601463","display_name":"SAFER","level":2,"score":0.5191737413406372},{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.5063928365707397},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.5050082802772522},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4903557300567627},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.461032897233963},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.43543022871017456},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.41732877492904663},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4110843241214752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3451891243457794},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3336334228515625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22990307211875916},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19636783003807068},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11659941077232361},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce50665.2020.9291862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce50665.2020.9291862","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":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/1","display_name":"No poverty"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2241154402","https://openalex.org/W2611328865","https://openalex.org/W3110635929"],"related_works":["https://openalex.org/W2952489973","https://openalex.org/W2106005123","https://openalex.org/W4300776969","https://openalex.org/W3152273675","https://openalex.org/W2266965707","https://openalex.org/W2108753466","https://openalex.org/W2084983808","https://openalex.org/W2906317811","https://openalex.org/W4318564253","https://openalex.org/W2402491700"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,23],"method":[4,109],"for":[5],"estimating":[6],"visibility":[7,33,38,77],"level":[8,39],"based":[9,99],"on":[10,82,100],"low":[11,101],"rank":[12,102],"matrix":[13,88,103],"completion":[14],"using":[15],"the":[16,26,64,68,91],"positional":[17],"relationship":[18],"of":[19,107],"GPV":[20],"data.":[21,115],"On":[22],"snowy":[24],"day,":[25],"driving":[27],"tasks":[28],"can":[29],"be":[30,48],"hard":[31],"because":[32],"is":[34],"poor.":[35],"By":[36],"providing":[37],"to":[40,59,87,90],"drivers":[41],"and":[42,76],"road":[43],"manager,":[44],"safer":[45],"traffic":[46],"will":[47],"realized.":[49],"To":[50],"estimate":[51],"visibility,":[52,60],"weather":[53],"data,":[54],"which":[55],"are":[56,61,85,97,110],"significantly":[57],"related":[58],"used":[62],"in":[63],"proposed":[65,69],"method.":[66],"In":[67],"method,":[70],"Grid":[71],"Point":[72],"Value":[73],"(GPV)":[74],"data":[75,78],"including":[79],"missing":[80,95],"values":[81,96],"unobserved":[83],"points":[84],"generated":[86],"corresponding":[89],"actual":[92,114],"location.":[93],"The":[94,105],"estimated":[98],"completion.":[104],"effectiveness":[106],"our":[108],"shown":[111],"by":[112],"utilizing":[113]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"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"}
