{"id":"https://openalex.org/W2990477556","doi":"https://doi.org/10.1109/access.2019.2953313","title":"An Automatic Detection and Identification Method of Welded Joints Based on Deep Neural Network","display_name":"An Automatic Detection and Identification Method of Welded Joints Based on Deep Neural Network","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2990477556","doi":"https://doi.org/10.1109/access.2019.2953313","mag":"2990477556"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2953313","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2953313","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08897647.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/ielx7/6287639/8600701/08897647.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100698159","display_name":"Lei Yang","orcid":"https://orcid.org/0000-0003-1212-9445"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Yang","raw_affiliation_strings":["Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","School of Electrical Engineering, Zhengzhou University, Zhengzhou"],"raw_orcid":"https://orcid.org/0000-0003-1212-9445","affiliations":[{"raw_affiliation_string":"Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006721216","display_name":"Yanhong Liu","orcid":"https://orcid.org/0000-0002-7349-5871"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhong Liu","raw_affiliation_strings":["Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","School of Electrical Engineering, Zhengzhou University, Zhengzhou"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081142499","display_name":"Jinzhu Peng","orcid":"https://orcid.org/0000-0002-2823-6571"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinzhu Peng","raw_affiliation_strings":["Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","School of Electrical Engineering, Zhengzhou University, Zhengzhou"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robot Perception and Control Engineering Laboratory, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Electrical Engineering, Zhengzhou University, Zhengzhou","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100698159"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.6674,"has_fulltext":true,"cited_by_count":36,"citation_normalized_percentile":{"value":0.89462824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"7","issue":null,"first_page":"164952","last_page":"164961"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10834","display_name":"Welding Techniques and Residual Stresses","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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":0.9980000257492065,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/welding","display_name":"Welding","score":0.8240407109260559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7110469937324524},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6379647850990295},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6339072585105896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5988932847976685},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4843081533908844},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.46189936995506287},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.458670973777771},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4203091263771057},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36000925302505493},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3220142126083374},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18482324481010437}],"concepts":[{"id":"https://openalex.org/C19474535","wikidata":"https://www.wikidata.org/wiki/Q131172","display_name":"Welding","level":2,"score":0.8240407109260559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7110469937324524},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6379647850990295},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6339072585105896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5988932847976685},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4843081533908844},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.46189936995506287},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.458670973777771},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4203091263771057},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36000925302505493},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3220142126083374},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18482324481010437},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2953313","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2953313","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08897647.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:c5786f24a92c49f3ac744de1c32e19ea","is_oa":true,"landing_page_url":"https://doaj.org/article/c5786f24a92c49f3ac744de1c32e19ea","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"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 7, Pp 164952-164961 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2953313","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2953313","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08897647.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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G1084493179","display_name":null,"funder_award_id":"61773351","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2163111087","display_name":null,"funder_award_id":"61473265","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3826403379","display_name":null,"funder_award_id":"17IRTSTHN013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8422024109","display_name":null,"funder_award_id":"61803344","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990477556.pdf","grobid_xml":"https://content.openalex.org/works/W2990477556.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1616262590","https://openalex.org/W1847108672","https://openalex.org/W1970352578","https://openalex.org/W1977633459","https://openalex.org/W2056969690","https://openalex.org/W2090673273","https://openalex.org/W2141697870","https://openalex.org/W2155669845","https://openalex.org/W2173520492","https://openalex.org/W2250461676","https://openalex.org/W2289500379","https://openalex.org/W2333169309","https://openalex.org/W2474320072","https://openalex.org/W2506764481","https://openalex.org/W2511276901","https://openalex.org/W2515637793","https://openalex.org/W2517582325","https://openalex.org/W2549196305","https://openalex.org/W2570343428","https://openalex.org/W2593332721","https://openalex.org/W2619004999","https://openalex.org/W2727628648","https://openalex.org/W2733639047","https://openalex.org/W2748302673","https://openalex.org/W2763853382","https://openalex.org/W2767241034","https://openalex.org/W2774434529","https://openalex.org/W2781645487","https://openalex.org/W2789987805","https://openalex.org/W2795535209","https://openalex.org/W2796347433","https://openalex.org/W2898371712","https://openalex.org/W2909813189","https://openalex.org/W2910693158","https://openalex.org/W2916908229","https://openalex.org/W2917609910","https://openalex.org/W2947613466","https://openalex.org/W2950069190","https://openalex.org/W2962750014","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2962968458","https://openalex.org/W2963037989","https://openalex.org/W2963073614","https://openalex.org/W2963684088","https://openalex.org/W2963785061","https://openalex.org/W2966407635","https://openalex.org/W3102431071","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6685352114","https://openalex.org/W6750227808","https://openalex.org/W6757146666"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2262409920","https://openalex.org/W3192220280","https://openalex.org/W2514640320","https://openalex.org/W2549651119","https://openalex.org/W2393201117","https://openalex.org/W1995340519","https://openalex.org/W4220851919","https://openalex.org/W2969591342","https://openalex.org/W2356243972"],"abstract_inverted_index":{"Welding":[0],"quality":[1,10,25,47,53],"is":[2,27,64,138],"an":[3],"important":[4,66],"factor":[5],"to":[6,140],"affect":[7,19],"the":[8,20,35,43,52,58,78,110,125,132,143,153,163,170,181,189,198,204],"performance,":[9],"and":[11,16,37,56,90,96,120,155,186,191,206],"strength":[12],"of":[13,31,39,45,73,81,99,112,135,157,173,194,209],"different":[14],"products,":[15],"it":[17],"will":[18],"safe":[21],"production.":[22,33],"Therefore,":[23],"welding":[24,46,74],"detection":[26,36,54,59,95,154,190,205],"a":[28,94],"key":[29],"process":[30],"industrial":[32,82,211],"And":[34],"identification":[38,63,97,156,192,207],"welded":[40,100,158,195],"joints":[41,101,159],"are":[42,129,160],"premise":[44],"detection,":[48],"which":[49,167],"could":[50,148,168,184,201],"reduce":[51],"range":[55],"improve":[57],"precision.":[60],"Welded":[61],"joint":[62],"also":[65],"for":[67,70],"providing":[68],"information":[69],"automatic":[71],"control":[72],"process.":[75],"Faced":[76],"with":[77,117],"complex":[79,210],"characteristics":[80],"environment,":[83],"such":[84],"as":[85],"weak":[86,88],"texture,":[87],"contrast":[89],"corrosion,":[91],"we":[92],"propose":[93],"method":[98,183,200],"based":[102],"on":[103],"deep":[104,144,164],"neural":[105,145,165],"network.":[106],"Firstly,":[107],"aimed":[108],"at":[109],"problem":[111],"insufficient":[113],"training":[114,127,136],"samples,":[115],"combined":[116],"image":[118],"processing":[119],"Generative":[121],"Adversarial":[122],"Network":[123],"(GAN),":[124],"high-quality":[126],"samples":[128,137],"generated.":[130],"Secondly,":[131],"updating":[133],"mechanism":[134],"established":[139],"guarantee":[141],"that":[142,180],"network":[146,166],"model":[147],"cover":[149],"all":[150],"samples.":[151],"Finally,":[152],"realized":[161],"by":[162],"avoid":[169],"handcrafted":[171],"features":[172],"conventional":[174],"machine":[175],"learning":[176],"methods.":[177],"Experiments":[178],"show":[179],"proposed":[182,199],"quickly":[185],"efficiently":[187],"finish":[188],"task":[193],"joints.":[196],"Meanwhile,":[197],"well":[202],"solve":[203],"problems":[208],"environment.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
