{"id":"https://openalex.org/W4200520585","doi":"https://doi.org/10.1109/iccais52680.2021.9624670","title":"Defect detection algorithm of wire rope based on color segmentation and Faster RCNN","display_name":"Defect detection algorithm of wire rope based on color segmentation and Faster RCNN","publication_year":2021,"publication_date":"2021-10-14","ids":{"openalex":"https://openalex.org/W4200520585","doi":"https://doi.org/10.1109/iccais52680.2021.9624670"},"language":"en","primary_location":{"id":"doi:10.1109/iccais52680.2021.9624670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais52680.2021.9624670","pdf_url":null,"source":{"id":"https://openalex.org/S4363608071","display_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","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/A5100735956","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-6318-401X"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049412988","display_name":"Tianxin Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxin Dong","raw_affiliation_strings":["School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004002278","display_name":"Haibin Shi","orcid":"https://orcid.org/0000-0002-2531-4730"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haibin Shi","raw_affiliation_strings":["North Company of China Construction, Second Engineering Bureau Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Company of China Construction, Second Engineering Bureau Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101618341","display_name":"Lei Ye","orcid":"https://orcid.org/0000-0002-3092-4031"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Ye","raw_affiliation_strings":["School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100735956"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":6.189,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.97916667,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"656","last_page":"661"},"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":0.9781000018119812,"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":0.9781000018119812,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wire-rope","display_name":"Wire rope","score":0.9047550559043884},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6258754134178162},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.531414806842804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.50130295753479},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4906271994113922},{"id":"https://openalex.org/keywords/extrusion","display_name":"Extrusion","score":0.47964340448379517},{"id":"https://openalex.org/keywords/rope","display_name":"Rope","score":0.4633399248123169},{"id":"https://openalex.org/keywords/deformation","display_name":"Deformation (meteorology)","score":0.45808449387550354},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4519372880458832},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4328323006629944},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41358864307403564},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40643468499183655},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.40353310108184814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3395887017250061},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.3195110857486725},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24499115347862244},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.11869567632675171}],"concepts":[{"id":"https://openalex.org/C2781373598","wikidata":"https://www.wikidata.org/wiki/Q552034","display_name":"Wire rope","level":2,"score":0.9047550559043884},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6258754134178162},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.531414806842804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.50130295753479},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4906271994113922},{"id":"https://openalex.org/C2778958987","wikidata":"https://www.wikidata.org/wiki/Q139143","display_name":"Extrusion","level":2,"score":0.47964340448379517},{"id":"https://openalex.org/C162269090","wikidata":"https://www.wikidata.org/wiki/Q1156047","display_name":"Rope","level":2,"score":0.4633399248123169},{"id":"https://openalex.org/C204366326","wikidata":"https://www.wikidata.org/wiki/Q3027650","display_name":"Deformation (meteorology)","level":2,"score":0.45808449387550354},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4519372880458832},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4328323006629944},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41358864307403564},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40643468499183655},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.40353310108184814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3395887017250061},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3195110857486725},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24499115347862244},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.11869567632675171}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccais52680.2021.9624670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais52680.2021.9624670","pdf_url":null,"source":{"id":"https://openalex.org/S4363608071","display_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Control, Automation and Information Sciences (ICCAIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W3118660043","https://openalex.org/W3162723853","https://openalex.org/W3180896826"],"related_works":["https://openalex.org/W1561243206","https://openalex.org/W2384089869","https://openalex.org/W2393914195","https://openalex.org/W2067650447","https://openalex.org/W2100539263","https://openalex.org/W2305196143","https://openalex.org/W2373023357","https://openalex.org/W2367592283","https://openalex.org/W2073570702","https://openalex.org/W1987425653"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,54,64,68,86,94,101,106,111,123,127],"four":[3],"common":[4],"types":[5],"of":[6,67,105,114,126],"wire":[7,20,24,27,55,69,115],"rope":[8,28,116],"defects":[9],"in":[10,96],"tower":[11,128],"crane":[12],"operation,":[13],"such":[14],"as":[15,75],"deformation,":[16],"core":[17],"extrusion,":[18],"steel":[19],"extrusion":[21],"and":[22,36],"surface":[23],"breakage,":[25],"a":[26,60],"defect":[29,95],"detection":[30,103],"algorithm":[31,49,107],"based":[32],"on":[33],"color":[34,47],"segmentation":[35,48],"faster":[37],"region":[38],"convolution":[39],"neural":[40],"networks":[41],"(Faster":[42],"RCNN)":[43],"is":[44,50,59,72,80,90],"proposed.":[45],"The":[46],"used":[51,91],"to":[52],"extract":[53],"rope,":[56,70],"if":[57,78],"there":[58,79],"big":[61],"difference":[62,82],"from":[63],"normal":[65],"shape":[66],"it":[71],"directly":[73],"judged":[74],"deformation":[76],"defect;":[77],"no":[81],"or":[83],"small":[84],"difference,":[85],"Faster":[87],"RCNN":[88],"network":[89],"for":[92],"detecting":[93],"detail.":[97],"Experiments":[98],"show":[99],"that":[100],"average":[102],"accuracy":[104],"reaches":[108],"90.61":[109],"%,":[110],"defective":[112],"parts":[113],"can":[117],"be":[118],"detected":[119],"effectively,":[120],"thereby":[121],"ensuring":[122],"safe":[124],"operation":[125],"crane.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}
