{"id":"https://openalex.org/W3083919065","doi":"https://doi.org/10.1109/access.2020.3022405","title":"Machine Vision Inspection of Electrical Connectors Based on Improved Yolo v3","display_name":"Machine Vision Inspection of Electrical Connectors Based on Improved Yolo v3","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3083919065","doi":"https://doi.org/10.1109/access.2020.3022405","mag":"3083919065"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3022405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187661.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187661.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101941676","display_name":"Weihao Wu","orcid":"https://orcid.org/0000-0001-6239-2984"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihao Wu","raw_affiliation_strings":["National Key Laboratory of Disaster Detection Technology and Instruments, China Jiliang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6239-2984","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Disaster Detection Technology and Instruments, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100634596","display_name":"Qing Li","orcid":"https://orcid.org/0000-0001-6073-1241"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["National Key Laboratory of Disaster Detection Technology and Instruments, China Jiliang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6073-1241","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Disaster Detection Technology and Instruments, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101941676"],"corresponding_institution_ids":["https://openalex.org/I55538621"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.5993,"has_fulltext":true,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96019381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"166184","last_page":"166196"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9847000241279602,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.9824000000953674,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6831278204917908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6271382570266724},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5917395949363708},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.539443850517273},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5312886834144592},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5258054137229919},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5192378163337708},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4730222225189209},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.460082083940506},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41402125358581543},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20579656958580017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13145986199378967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6831278204917908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6271382570266724},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5917395949363708},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.539443850517273},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5312886834144592},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5258054137229919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5192378163337708},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4730222225189209},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.460082083940506},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41402125358581543},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20579656958580017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13145986199378967},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3022405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187661.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7919ea3759d44503bc43396fd0310550","is_oa":true,"landing_page_url":"https://doaj.org/article/7919ea3759d44503bc43396fd0310550","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 166184-166196 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3022405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187661.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3083919065.pdf","grobid_xml":"https://content.openalex.org/works/W3083919065.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1972556843","https://openalex.org/W1981319256","https://openalex.org/W1989042553","https://openalex.org/W1995258167","https://openalex.org/W2033890762","https://openalex.org/W2043654250","https://openalex.org/W2076063813","https://openalex.org/W2144172034","https://openalex.org/W2213443318","https://openalex.org/W2329613113","https://openalex.org/W2349359698","https://openalex.org/W2406523001","https://openalex.org/W2533800772","https://openalex.org/W2570343428","https://openalex.org/W2585123518","https://openalex.org/W2592929672","https://openalex.org/W2593889865","https://openalex.org/W2760798442","https://openalex.org/W2795535209","https://openalex.org/W2808919226","https://openalex.org/W2897125295","https://openalex.org/W2909756869","https://openalex.org/W2939193868","https://openalex.org/W2940791172","https://openalex.org/W2953034244","https://openalex.org/W2962752334","https://openalex.org/W2963037989","https://openalex.org/W2963237621","https://openalex.org/W2963372888","https://openalex.org/W2976842945","https://openalex.org/W3106250896","https://openalex.org/W3203808378","https://openalex.org/W4245617538","https://openalex.org/W4293584584","https://openalex.org/W6681239517","https://openalex.org/W6750227808","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2498789492","https://openalex.org/W2521347458","https://openalex.org/W2729981612","https://openalex.org/W4233449973","https://openalex.org/W2925692864","https://openalex.org/W2768526084","https://openalex.org/W1996690921"],"abstract_inverted_index":{"Aiming":[0],"at":[1,66],"the":[2,38,49,68,72,78,85,90,98,105,112,118,123,129,167,174,197,202,207,218,262,265],"problems":[3],"of":[4,52,59,89,163,166,206,234,237,244,264],"electrical":[5,34,208,238,269],"connector":[6,35,270],"defect":[7,232],"detection,":[8],"such":[9],"as":[10],"low":[11,13],"automation,":[12],"detection":[14,17,69,121,131,158,181,188,233],"accuracy,":[15],"slow":[16],"speed,":[18],"and":[19,97,147,201,212,229,259],"poor":[20],"robustness,":[21],"an":[22,241],"improved":[23,219],"Yolo":[24,220,255],"v3":[25,221,256],"algorithm":[26,41,222],"was":[27],"proposed":[28,191],"in":[29,75,159,223],"this":[30,53,76,160,224],"paper":[31,54,161,225],"to":[32,44,55,116,135,143,182],"detect":[33],"defects.":[36],"First,":[37],"K-means":[39],"clustering":[40],"is":[42,93,102,190,247,257],"used":[43],"perform":[45],"cluster":[46],"analysis":[47],"on":[48],"data":[50],"set":[51],"obtain":[56,117],"three":[57],"kinds":[58],"candidate":[60],"frames":[61],"with":[62,104,240],"aspect":[63],"ratios,":[64],"aiming":[65],"improving":[67],"accuracy":[70,242],"for":[71,156,192,231,268],"defective":[73],"objects":[74],"paper;":[77],"8-fold":[79],"downsampled":[80,107],"feature":[81,100,108,120,145,152],"map":[82,101,109],"outputted":[83,110],"by":[84,111,128],"third":[86],"residual":[87,114,141],"block":[88,115],"backbone":[91],"network":[92],"upsampled":[94],"4":[95],"times,":[96],"obtained":[99],"merged":[103],"2-fold":[106],"second":[113],"fusion":[119],"layer;":[122],"6":[124],"DBL":[125,137],"units":[126,142],"passed":[127],"target":[130,157],"layer":[132],"are":[133,154],"changed":[134],"2":[136,140],"unit":[138],"plus":[139],"improve":[144],"reuse":[146],"acquisition;":[148],"In":[149],"addition,":[150],"single-scale":[151],"maps":[153],"chose":[155],"instead":[162],"multi-scale":[164],"prediction":[165],"original":[168,254],"network,":[169],"which":[170,246],"not":[171],"only":[172],"saves":[173],"calculation":[175],"amount,":[176],"but":[177],"also":[178],"avoids":[179],"false":[180],"a":[183],"certain":[184],"extent.;":[185],"A":[186],"new":[187],"method":[189],"relative":[193],"rotation":[194],"defects":[195],"between":[196],"inner":[198],"ring":[199,204],"area":[200,205],"outer":[203],"connector.":[209],"The":[210,253],"qualitative":[211],"quantitative":[213],"experimental":[214],"results":[215],"show":[216],"that":[217],"has":[226],"better":[227],"performance":[228],"speed":[230],"various":[235],"types":[236],"connectors,":[239],"rate":[243],"93.5%,":[245],"more":[248],"accurate":[249],"than":[250],"Faster":[251],"R-CNN.":[252],"faster":[258],"basically":[260],"meets":[261],"requirements":[263],"industrial":[266],"field":[267],"testing.":[271]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":8}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
