{"id":"https://openalex.org/W2899280016","doi":"https://doi.org/10.1109/tim.2018.2868490","title":"Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning","display_name":"Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning","publication_year":2018,"publication_date":"2018-10-31","ids":{"openalex":"https://openalex.org/W2899280016","doi":"https://doi.org/10.1109/tim.2018.2868490","mag":"2899280016"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2018.2868490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2018.2868490","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5070795080","display_name":"Gaoqiang Kang","orcid":"https://orcid.org/0000-0002-1196-2614"},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gaoqiang Kang","raw_affiliation_strings":["School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, China","institution_ids":["https://openalex.org/I13985625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063101827","display_name":"Shibin Gao","orcid":"https://orcid.org/0000-0001-7753-202X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibin Gao","raw_affiliation_strings":["School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004040039","display_name":"Long Yu","orcid":"https://orcid.org/0000-0002-5481-8030"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Yu","raw_affiliation_strings":["School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052233785","display_name":"Dongkai Zhang","orcid":"https://orcid.org/0000-0002-9050-2447"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongkai Zhang","raw_affiliation_strings":["School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070795080"],"corresponding_institution_ids":["https://openalex.org/I13985625"],"apc_list":null,"apc_paid":null,"fwci":22.1105,"has_fulltext":false,"cited_by_count":264,"citation_normalized_percentile":{"value":0.99836214,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"68","issue":"8","first_page":"2679","last_page":"2690"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9983999729156494,"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"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9983999729156494,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9947999715805054,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9858999848365784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7734507322311401},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6416645050048828},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5419846177101135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5158954858779907},{"id":"https://openalex.org/keywords/insulator","display_name":"Insulator (electricity)","score":0.48550036549568176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4059465527534485},{"id":"https://openalex.org/keywords/automotive-engineering","display_name":"Automotive engineering","score":0.33215513825416565},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3291482627391815},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3236808776855469},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.288812518119812}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7734507322311401},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6416645050048828},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5419846177101135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5158954858779907},{"id":"https://openalex.org/C212702","wikidata":"https://www.wikidata.org/wiki/Q178150","display_name":"Insulator (electricity)","level":2,"score":0.48550036549568176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4059465527534485},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.33215513825416565},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3291482627391815},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3236808776855469},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.288812518119812}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2018.2868490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2018.2868490","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8778789598","display_name":null,"funder_award_id":"U1434203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1601124178","https://openalex.org/W1978459068","https://openalex.org/W2008317417","https://openalex.org/W2022508996","https://openalex.org/W2040483045","https://openalex.org/W2069747077","https://openalex.org/W2095705004","https://openalex.org/W2100495367","https://openalex.org/W2102605133","https://openalex.org/W2122646361","https://openalex.org/W2125148312","https://openalex.org/W2155033980","https://openalex.org/W2161969291","https://openalex.org/W2165991108","https://openalex.org/W2191848209","https://openalex.org/W2341058432","https://openalex.org/W2406523001","https://openalex.org/W2508088778","https://openalex.org/W2528351807","https://openalex.org/W2555344168","https://openalex.org/W2555875178","https://openalex.org/W2570343428","https://openalex.org/W2586457790","https://openalex.org/W2768731046","https://openalex.org/W2770740228","https://openalex.org/W2772386856","https://openalex.org/W2794282829","https://openalex.org/W2914746235","https://openalex.org/W2963037989","https://openalex.org/W3106250896","https://openalex.org/W4239943352","https://openalex.org/W4247680705","https://openalex.org/W6674330103","https://openalex.org/W6750335474","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000","https://openalex.org/W3037110488"],"abstract_inverted_index":{"The":[0,100,158],"insulator":[1,30,58,88,175],"is":[2,61,112,146,161],"an":[3],"important":[4],"catenary":[5,13,35,118,174],"component":[6],"that":[7,124,145,185],"maintains":[8],"the":[9,12,18,25,29,48,67,73,116,121,126,131,165,173,179,186],"insulation":[10],"between":[11],"and":[14,24,40,72,120,134,153,168],"earth.":[15],"Due":[16],"to":[17,46,66,114],"long-term":[19],"impact":[20],"of":[21,50,57,70,76,104,148,172],"railway":[22,51,182],"vehicles":[23],"environment,":[26],"defects":[27,71],"in":[28],"are":[31,128,137],"inevitable.":[32],"Recently,":[33],"automatic":[34],"inspection":[36],"using":[37,93],"computer":[38],"vision":[39],"pattern":[41],"recognition":[42],"has":[43],"been":[44],"introduced":[45],"improve":[47],"safety":[49],"operation.":[52],"However,":[53],"achieving":[54],"full":[55],"automation":[56],"defect":[59,90,159,176],"detection":[60,91,177,191],"still":[62],"very":[63],"challenging":[64],"due":[65],"visual":[68],"complexity":[69],"small":[74],"number":[75],"defective":[77],"insulators.":[78],"To":[79],"overcome":[80],"these":[81],"problems,":[82],"this":[83],"paper":[84],"proposes":[85],"a":[86,94,108,140,149,154],"novel":[87],"surface":[89],"system":[92,102,187],"deep":[95,141,150,155],"convolutional":[96],"neural":[97,143],"network":[98,111,144],"(CNN).":[99],"proposed":[101],"consists":[103],"two":[105],"stages.":[106],"First,":[107],"Faster":[109],"R-CNN":[110],"adopted":[113],"localize":[115],"key":[117],"components,":[119],"image":[122],"areas":[123],"contain":[125],"insulators":[127],"obtained.":[129],"Then,":[130],"classification":[132,166],"score":[133,136,167],"anomaly":[135,169],"determined":[138,162],"from":[139],"multitask":[142],"composed":[147],"material":[151],"classifier":[152],"denoising":[156],"autoencoder.":[157],"state":[160],"by":[163],"analyzing":[164],"score.":[170],"Experiments":[171],"along":[178],"Hefei-Fuzhou":[180],"high-speed":[181],"line":[183],"indicate":[184],"can":[188],"achieve":[189],"high":[190],"accuracy.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":41},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":49},{"year":2021,"cited_by_count":50},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":17}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
