{"id":"https://openalex.org/W3009059331","doi":"https://doi.org/10.1109/icsai48974.2019.9010467","title":"A Variational Bayesian Inference with Small Dataset for High-Precision Infrared Thermal Imaging","display_name":"A Variational Bayesian Inference with Small Dataset for High-Precision Infrared Thermal Imaging","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3009059331","doi":"https://doi.org/10.1109/icsai48974.2019.9010467","mag":"3009059331"},"language":"en","primary_location":{"id":"doi:10.1109/icsai48974.2019.9010467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai48974.2019.9010467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Systems and Informatics (ICSAI)","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/A5050267843","display_name":"Ning Chu","orcid":"https://orcid.org/0000-0003-1514-873X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]},{"id":"https://openalex.org/I4210106357","display_name":"Zhejiang Energy Research Institute","ror":"https://ror.org/01fqrb109","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106357"]},{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ning Chu","raw_affiliation_strings":["College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","institution_ids":["https://openalex.org/I4210106357","https://openalex.org/I4210132615"]},{"raw_affiliation_string":"Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037115676","display_name":"Yaochun Hou","orcid":"https://orcid.org/0000-0002-2071-1331"},"institutions":[{"id":"https://openalex.org/I4210106357","display_name":"Zhejiang Energy Research Institute","ror":"https://ror.org/01fqrb109","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106357"]},{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaochun Hou","raw_affiliation_strings":["College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","institution_ids":["https://openalex.org/I4210106357","https://openalex.org/I4210132615"]},{"raw_affiliation_string":"Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075505513","display_name":"Dazhuan Wu","orcid":"https://orcid.org/0000-0003-1439-2386"},"institutions":[{"id":"https://openalex.org/I4210132615","display_name":"Zhejiang Energy Group (China)","ror":"https://ror.org/03a2tkf74","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210132615"]},{"id":"https://openalex.org/I4210106357","display_name":"Zhejiang Energy Research Institute","ror":"https://ror.org/01fqrb109","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210106357"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dazhuan Wu","raw_affiliation_strings":["College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Energy Engineering, Zhejiang University, Zheda road 38, Hangzhou, China","institution_ids":["https://openalex.org/I4210106357","https://openalex.org/I4210132615"]},{"raw_affiliation_string":"Zhejiang University [Hangzhou, China] (866 Yuhangtang Road * Hangzhou * Zhejiang Province * 310058 * P. R. China - China)","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106037612","display_name":"Ali Mohammed Djafari","orcid":null},"institutions":[{"id":"https://openalex.org/I4210097418","display_name":"Laboratoire des signaux et syst\u00e8mes","ror":"https://ror.org/00skw9v43","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I277688954","https://openalex.org/I277688954","https://openalex.org/I4210097418","https://openalex.org/I4210107720"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210107720","display_name":"CentraleSup\u00e9lec","ror":"https://ror.org/019tcpt25","country_code":"FR","type":"facility","lineage":["https://openalex.org/I277688954","https://openalex.org/I4210107720"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ali Mohammed Djafari","raw_affiliation_strings":["Lab of Signals and Systems (LSS), UMR 8506 CNRS-CentraleSupelec-Univ Paris Sud, 3 rue Joliot Curie, Gif-sur-Yvette, France","L2S - Laboratoire des signaux et syst\u00e8mes (Plateau de Moulon 3 rue Joliot Curie 91192 GIF SUR YVETTE CEDEX - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Lab of Signals and Systems (LSS), UMR 8506 CNRS-CentraleSupelec-Univ Paris Sud, 3 rue Joliot Curie, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I4210107720","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"L2S - Laboratoire des signaux et syst\u00e8mes (Plateau de Moulon 3 rue Joliot Curie 91192 GIF SUR YVETTE CEDEX - France)","institution_ids":["https://openalex.org/I4210097418"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050267843"],"corresponding_institution_ids":["https://openalex.org/I4210106357","https://openalex.org/I4210132615","https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.3661,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59615191,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1190","last_page":"1195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T12019","display_name":"Calibration and Measurement Techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/prior-probability","display_name":"Prior probability","score":0.7863273024559021},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6790357232093811},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.6665092706680298},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6518099308013916},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5735897421836853},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45305293798446655},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4472789764404297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3853972554206848}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7863273024559021},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6790357232093811},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.6665092706680298},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518099308013916},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5735897421836853},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45305293798446655},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4472789764404297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3853972554206848},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icsai48974.2019.9010467","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai48974.2019.9010467","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04488497v1","is_oa":false,"landing_page_url":"https://centralesupelec.hal.science/hal-04488497","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019 6th International Conference on Systems and Informatics (ICSAI), Nov 2019, Shanghai, France. pp.1190-1195, &#x27E8;10.1109/ICSAI48974.2019.9010467&#x27E9;","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1990984447","https://openalex.org/W1993663732","https://openalex.org/W2007804484","https://openalex.org/W2053429032","https://openalex.org/W2059076510","https://openalex.org/W2088886701","https://openalex.org/W2141125852","https://openalex.org/W2546382135","https://openalex.org/W2811165342","https://openalex.org/W2811298999","https://openalex.org/W2912451899","https://openalex.org/W2944090748","https://openalex.org/W2947220227","https://openalex.org/W2957772095","https://openalex.org/W3034565885","https://openalex.org/W3100515397","https://openalex.org/W4288616894","https://openalex.org/W4301867415"],"related_works":["https://openalex.org/W2562263695","https://openalex.org/W2135187896","https://openalex.org/W2147201983","https://openalex.org/W2015518264","https://openalex.org/W2795035211","https://openalex.org/W2160108762","https://openalex.org/W1718066205","https://openalex.org/W2017034551","https://openalex.org/W2793406240","https://openalex.org/W2164129707"],"abstract_inverted_index":{"Recently":[0],"infrared":[1,242],"thermal":[2,13,94,228,246,285],"imaging":[3,32,247],"with":[4,48],"high-precision":[5],"has":[6,259],"been":[7],"widely":[8],"investigated":[9],"to":[10,53,103,194,212,281],"detect":[11,283],"abnormal":[12,93,284],"defects":[14],"caused":[15],"by":[16,231],"current":[17],"leakage,":[18],"component":[19],"heating":[20],"and":[21,36,64,96,110,162,184,191,196,236,251,269,277],"temperature":[22,117],"fluctuation":[23],"etc.":[24,254],"However,":[25],"two":[26],"major":[27],"factors":[28],"seriously":[29],"limit":[30],"the":[31,55,59,78,105,123,132,147,181,219,224,233,260],"precision:":[33],"measure":[34],"uncertainty":[35,106,225],"small":[37],"dataset.":[38],"Therefore,":[39],"this":[40],"paper":[41],"presents":[42],"a":[43,240],"variational":[44],"Bayesian":[45,84],"inference":[46],"(VBI)":[47],"sparsity-enforcing":[49,148],"prior":[50,90,135,182],"so":[51],"as":[52],"solve":[54],"above":[56],"challenges.":[57],"Though":[58],"sampled":[60],"information":[61],"is":[62,279],"incomplete":[63],"measurement":[65,100],"error":[66],"are":[67,82,210],"not":[68,120],"trivial,":[69],"especially":[70],"in":[71,144,158,215],"fault":[72],"diagnosis":[73],"of":[74,80,115,126,134,146,152,165,200,226,245,262],"electrical":[75,127],"power":[76],"system,":[77],"advantages":[79,261],"VBI":[81,258],"that":[83,256],"cost":[85,185],"function":[86,186],"will":[87,119,141,167,187],"still":[88],"combine":[89],"model":[91,98,136,183,230,234],"(of":[92,99],"source)":[95],"likelihood":[97],"errors)":[101],"together":[102],"regulate":[104],"from":[107],"both":[108,180],"physics":[109],"measurements.":[111],"Meanwhile,":[112],"sparsity":[113,139],"priors":[114,140],"irregular":[116],"features":[118],"only":[121,202],"embody":[122],"health":[124],"characteristics":[125],"device,":[128],"but":[129],"also":[130],"reduce":[131],"dimension":[133],"parameters.":[137],"Such":[138],"be":[142,155,168,188,213],"modelled":[143],"terms":[145],"distributions.":[149],"Indeed,":[150],"most":[151],"signals":[153],"can":[154,222],"sparsely":[156],"represented":[157],"certain":[159],"transformed":[160],"domain":[161],"key":[163],"knowledge":[164],"signatures":[166],"deeply":[169],"studied":[170],"using":[171],"sparse":[172],"samples":[173],"rather":[174],"than":[175],"condensed":[176],"data.":[177],"More":[178],"importantly,":[179],"trained":[189],"on-line":[190],"updated":[192],"according":[193],"actual":[195],"historical":[197],"data,":[198],"instead":[199],"replying":[201],"on":[203,248],"definite":[204],"mechanisms":[205],"or":[206],"empirical":[207],"rules":[208],"which":[209],"hard":[211],"adapted":[214],"industry":[216],"application.":[217],"Moreover,":[218],"proposed":[220,257],"method":[221],"calibrate":[223],"conventional":[227],"radiation":[229],"updating":[232],"hyper-parameters":[235],"latent":[237],"variables.":[238],"Through":[239],"moderate":[241],"sensor,":[243],"results":[244],"ABB":[249],"controllers":[250],"Schneider":[252],"switches":[253],"confirm":[255],"high-precision(<;":[263],"0.95":[264],"\u00b0C":[265],"),":[266],"far-field":[267],"detection(>2.0m)":[268],"fast":[270,282],"inspection":[271],"(<;":[272],".8s":[273],"for":[274],"160x120":[275],"pixels),":[276],"it":[278],"cost-effective":[280],"sources.":[286]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}
