{"id":"https://openalex.org/W2291773182","doi":"https://doi.org/10.1109/sii.2015.7405019","title":"A particle detection method using robust PCA","display_name":"A particle detection method using robust PCA","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2291773182","doi":"https://doi.org/10.1109/sii.2015.7405019","mag":"2291773182"},"language":"en","primary_location":{"id":"doi:10.1109/sii.2015.7405019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii.2015.7405019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/SICE International Symposium on System Integration (SII)","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/A5085923548","display_name":"Kenta Toyoda","orcid":null},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kenta Toyoda","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103163418","display_name":"Kazuhiro Hotta","orcid":"https://orcid.org/0000-0002-5675-8713"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Hotta","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I96636082"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085923548"],"corresponding_institution_ids":["https://openalex.org/I96636082"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18702076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"438","last_page":"442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9545000195503235,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6705888509750366},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6120334267616272},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6120112538337708},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5736026167869568},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5679234862327576},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5672592520713806},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5568816065788269},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48747992515563965},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45954105257987976},{"id":"https://openalex.org/keywords/background-image","display_name":"Background image","score":0.459500789642334},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.42206886410713196}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6705888509750366},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6120334267616272},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6120112538337708},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5736026167869568},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5679234862327576},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5672592520713806},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5568816065788269},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48747992515563965},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45954105257987976},{"id":"https://openalex.org/C3019635856","wikidata":"https://www.wikidata.org/wiki/Q1619726","display_name":"Background image","level":3,"score":0.459500789642334},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.42206886410713196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii.2015.7405019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii.2015.7405019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4000000059604645,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1513013675","https://openalex.org/W1736339626","https://openalex.org/W1960877884","https://openalex.org/W1969792798","https://openalex.org/W1982428585","https://openalex.org/W2044809283","https://openalex.org/W2047670868","https://openalex.org/W2104989842","https://openalex.org/W2145962650","https://openalex.org/W6675879561","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Currently,":[0],"the":[1,38,46,55,70,79,83,91,98,111,119,136,147],"inspection":[2],"of":[3,97],"asbestos":[4,23],"in":[5,144],"building":[6],"materials":[7],"has":[8],"been":[9],"done":[10],"manually":[11],"by":[12,50,61,128],"human":[13],"inspectors.":[14],"Inspectors":[15],"must":[16],"count":[17],"3,000":[18,30],"particles":[19,31,48,66,140],"to":[20,94,109],"judge":[21],"whether":[22],"is":[24,32,41],"included":[25],"or":[26],"not.":[27],"However,":[28,78],"counting":[29,39,49],"hard":[33],"jobs":[34],"for":[35],"inspectors":[36],"and":[37,65,75,86,113,133],"result":[40],"subjective.":[42],"Thus,":[43],"we":[44,87,102,124],"propose":[45],"automatic":[47],"computer.":[51],"Conventional":[52],"method":[53,80,127,138],"estimated":[54],"background":[56,76,112],"from":[57,69],"an":[58],"input":[59,74,99],"image":[60,72],"a":[62],"median":[63,92],"filter":[64,84,93,120],"are":[67],"detected":[68,139],"difference":[71],"between":[73],"images.":[77],"depends":[81],"on":[82,118],"sizes":[85],"can":[88],"not":[89],"apply":[90],"peripheral":[95],"regions":[96],"image.":[100],"Therefore,":[101],"use":[103],"robust":[104],"Principal":[105],"Component":[106],"Analysis":[107],"(PCA)":[108],"estimate":[110],"outlier":[114],"(particle)":[115],"without":[116],"depending":[117],"sizes.":[121],"In":[122],"experiments,":[123],"evaluate":[125],"our":[126],"using":[129],"19":[130],"microscope":[131],"images":[132],"confirmed":[134],"that":[135],"proposed":[137],"with":[141,146],"higher":[142],"accuracy":[143],"comparison":[145],"conventional":[148],"method.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}