{"id":"https://openalex.org/W3176931625","doi":"https://doi.org/10.1109/i2mtc50364.2021.9460081","title":"Production of Data Set Based on Adjustable Rotary Table and Part Identification Based on Deep Learning","display_name":"Production of Data Set Based on Adjustable Rotary Table and Part Identification Based on Deep Learning","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3176931625","doi":"https://doi.org/10.1109/i2mtc50364.2021.9460081","mag":"3176931625"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc50364.2021.9460081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9460081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5008465811","display_name":"Yihan Meng","orcid":null},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yihan Meng","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014092608","display_name":"He Xu","orcid":"https://orcid.org/0000-0003-3333-2880"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Xu","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027063174","display_name":"Zhen Ma","orcid":"https://orcid.org/0000-0001-6855-4622"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Ma","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028484596","display_name":"Jiaqiang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqiang Zhou","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079725418","display_name":"Daquan Hui","orcid":null},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Daquan Hui","raw_affiliation_strings":["College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China"],"affiliations":[{"raw_affiliation_string":"College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5008465811"],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10163967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.767985463142395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5746952295303345},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5488853454589844},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5430914163589478},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5319666266441345},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5236601233482361},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5034844279289246},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5016460418701172},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43898388743400574},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4387189745903015},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.42409634590148926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.415205180644989},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40542760491371155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.767985463142395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5746952295303345},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5488853454589844},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5430914163589478},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5319666266441345},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5236601233482361},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5034844279289246},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5016460418701172},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43898388743400574},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4387189745903015},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.42409634590148926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.415205180644989},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40542760491371155},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc50364.2021.9460081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc50364.2021.9460081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G1126643094","display_name":null,"funder_award_id":"51875113","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":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2803897592","https://openalex.org/W2928048063","https://openalex.org/W2963037989","https://openalex.org/W2970285847","https://openalex.org/W2981916037","https://openalex.org/W3033274390","https://openalex.org/W3034848508","https://openalex.org/W3089875808","https://openalex.org/W3092780890","https://openalex.org/W3094968069","https://openalex.org/W4210257598"],"related_works":["https://openalex.org/W4285411112","https://openalex.org/W2085033728","https://openalex.org/W3132346564","https://openalex.org/W2991483587","https://openalex.org/W2786391746","https://openalex.org/W2914559142","https://openalex.org/W4226059458","https://openalex.org/W4381430104","https://openalex.org/W2995102745","https://openalex.org/W4225292444"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"great":[3],"progress":[4],"has":[5,38],"been":[6],"made":[7],"in":[8,17,80,93,147,168],"the":[9,18,21,25,31,47,87,91,123,130,137,148,157,162,166,169],"application":[10],"of":[11,24,49,66,90,144,165],"computer":[12],"vision":[13],"to":[14,46,57,96,106,121],"part":[15],"detection":[16,69,163],"industry.":[19],"With":[20],"rapid":[22],"development":[23],"neural":[26],"network,":[27],"it":[28,54],"gradually":[29],"replaced":[30],"traditional":[32],"artificial":[33],"feature":[34],"extraction":[35],"method":[36,65,118],"and":[37,51,110,129],"become":[39],"a":[40,59,64,108,115],"new":[41],"research":[42],"hotspot.":[43],"However,":[44],"due":[45],"diversity":[48],"parts":[50,92],"working":[52,132],"scenarios,":[53],"is":[55,78,119],"difficult":[56],"produce":[58],"common":[60],"data":[61,70,112,116,125,138],"set.":[62,113],"Therefore,":[63],"making":[67],"target":[68],"set":[71,126,139],"based":[72],"on":[73,156],"an":[74],"adjustable":[75],"rotary":[76,158],"table":[77],"proposed":[79],"this":[81],"paper,":[82],"which":[83,160],"can":[84,140],"uniformly":[85],"express":[86],"pixel":[88],"information":[89,128,146],"each":[94],"view":[95],"be":[97],"detected":[98],"with":[99],"as":[100,104],"few":[101],"training":[102],"samples":[103,154],"possible,":[105],"obtain":[107],"balanced":[109],"uniform":[111],"Besides,":[114],"augmented":[117],"used":[120],"synthesize":[122],"existing":[124],"annotation":[127],"actual":[131,149],"background":[133,145],"images,":[134],"so":[135],"that":[136],"contain":[141],"all":[142],"kinds":[143],"scene":[150],"only":[151],"after":[152],"collecting":[153],"once":[155],"table,":[159],"improves":[161],"performance":[164],"model":[167],"specific":[170],"conditions.":[171]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
