{"id":"https://openalex.org/W3137707937","doi":"https://doi.org/10.3390/s21062123","title":"FPGA-Based Acceleration on Additive Manufacturing Defects Inspection","display_name":"FPGA-Based Acceleration on Additive Manufacturing Defects Inspection","publication_year":2021,"publication_date":"2021-03-18","ids":{"openalex":"https://openalex.org/W3137707937","doi":"https://doi.org/10.3390/s21062123","mag":"3137707937","pmid":"https://pubmed.ncbi.nlm.nih.gov/33803530"},"language":"en","primary_location":{"id":"doi:10.3390/s21062123","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21062123","pdf_url":"https://www.mdpi.com/1424-8220/21/6/2123/pdf?version=1616286356","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/6/2123/pdf?version=1616286356","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082510499","display_name":"Yawen Luo","orcid":"https://orcid.org/0000-0002-1238-9231"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yawen Luo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA"],"raw_orcid":"https://orcid.org/0000-0002-1238-9231","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA","institution_ids":["https://openalex.org/I44461941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384521","display_name":"Yuhua Chen","orcid":"https://orcid.org/0000-0003-3218-1304"},"institutions":[{"id":"https://openalex.org/I44461941","display_name":"University of Houston","ror":"https://ror.org/048sx0r50","country_code":"US","type":"education","lineage":["https://openalex.org/I44461941"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuhua Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA"],"raw_orcid":"https://orcid.org/0000-0003-3218-1304","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA","institution_ids":["https://openalex.org/I44461941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082510499"],"corresponding_institution_ids":["https://openalex.org/I44461941"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.3011,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.78951647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"21","issue":"6","first_page":"2123","last_page":"2123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10783","display_name":"Additive Manufacturing and 3D Printing Technologies","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.9991999864578247,"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/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9896000027656555,"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8935920000076294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6434926986694336},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5976009964942932},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5454680323600769},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.542419970035553},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5062386393547058},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4963842034339905},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.46993526816368103},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.45245441794395447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4413602650165558},{"id":"https://openalex.org/keywords/gate-array","display_name":"Gate array","score":0.44113805890083313},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4284190535545349},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41810768842697144},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.37316060066223145},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.354754775762558},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.34284695982933044}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8935920000076294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6434926986694336},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5976009964942932},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5454680323600769},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.542419970035553},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5062386393547058},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4963842034339905},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.46993526816368103},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.45245441794395447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4413602650165558},{"id":"https://openalex.org/C114237110","wikidata":"https://www.wikidata.org/wiki/Q114901","display_name":"Gate array","level":3,"score":0.44113805890083313},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4284190535545349},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41810768842697144},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.37316060066223145},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.354754775762558},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.34284695982933044},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"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":5,"locations":[{"id":"doi:10.3390/s21062123","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21062123","pdf_url":"https://www.mdpi.com/1424-8220/21/6/2123/pdf?version=1616286356","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:33803530","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33803530","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:612b90b9166c4ac58eef2c42463c95cf","is_oa":true,"landing_page_url":"https://doaj.org/article/612b90b9166c4ac58eef2c42463c95cf","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":"Sensors, Vol 21, Iss 6, p 2123 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/6/2123/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21062123","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 6; Pages: 2123","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8003074","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8003074","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21062123","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21062123","pdf_url":"https://www.mdpi.com/1424-8220/21/6/2123/pdf?version=1616286356","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3137707937.pdf","grobid_xml":"https://content.openalex.org/works/W3137707937.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1567302070","https://openalex.org/W1595370658","https://openalex.org/W1969566657","https://openalex.org/W2025138352","https://openalex.org/W2088049833","https://openalex.org/W2092072518","https://openalex.org/W2129305389","https://openalex.org/W2145904766","https://openalex.org/W2155287007","https://openalex.org/W2168804568","https://openalex.org/W2183529453","https://openalex.org/W2606155622","https://openalex.org/W2612624696","https://openalex.org/W2765235648","https://openalex.org/W2767965164","https://openalex.org/W2787550496","https://openalex.org/W2885960709","https://openalex.org/W2894638366","https://openalex.org/W2904390180","https://openalex.org/W2944303778","https://openalex.org/W2950806363","https://openalex.org/W2951479717","https://openalex.org/W2963745697","https://openalex.org/W2968982355","https://openalex.org/W2981845603","https://openalex.org/W2996382986","https://openalex.org/W2999093589","https://openalex.org/W2999135634","https://openalex.org/W3005676042","https://openalex.org/W3007573493","https://openalex.org/W3015187397","https://openalex.org/W3128526753","https://openalex.org/W3128975304","https://openalex.org/W6656605171","https://openalex.org/W6686184986","https://openalex.org/W6774199647"],"related_works":["https://openalex.org/W2014165129","https://openalex.org/W2367348190","https://openalex.org/W594316872","https://openalex.org/W2831860248","https://openalex.org/W2367794224","https://openalex.org/W2072850836","https://openalex.org/W2017163657","https://openalex.org/W1968650434","https://openalex.org/W2105610663","https://openalex.org/W1996607072"],"abstract_inverted_index":{"Additive":[0],"manufacturing":[1],"(AM)":[2],"has":[3],"gained":[4],"increasing":[5],"attention":[6],"over":[7],"the":[8,47,52,56,62,66,108,114,119,130,137,149,157,161,197],"past":[9],"years":[10],"due":[11],"to":[12,27,45,60,82,105,127,183,215],"its":[13],"fast":[14],"prototype,":[15],"easier":[16],"modification,":[17],"and":[18,40,122,177,188,209],"possibility":[19],"for":[20,72,96,113,156],"complex":[21],"internal":[22,33],"texture":[23],"devices":[24],"when":[25],"compared":[26],"traditional":[28],"manufacture":[29],"processing.":[30],"However,":[31],"potential":[32],"defects":[34,63,67,84,204],"are":[35,94,125],"occurring":[36],"during":[37],"AM":[38],"processes,":[39],"it":[41,210],"requires":[42],"real-time":[43,87,203],"inspections":[44],"minimize":[46],"costs":[48],"by":[49],"either":[50],"aborting":[51],"processing":[53],"or":[54,153],"repairing":[55],"defect.":[57],"In":[58],"order":[59],"perform":[61,83,202],"inspection,":[64],"first":[65],"database":[68],"NEU-DET":[69,141],"is":[70,80,103,151,175,194],"used":[71],"training.":[73],"Then,":[74],"a":[75],"convolution":[76],"neural":[77,100],"network":[78,101],"(CNN)":[79],"applied":[81],"classification.":[85],"For":[86],"purposes,":[88],"Field":[89],"Programmable":[90],"Gate":[91],"Arrays":[92],"(FPGAs)":[93],"utilized":[95],"acceleration.":[97],"A":[98],"binarized":[99],"(BNN)":[102],"proposed":[104,198],"best":[106],"fit":[107],"FPGA":[109,217],"bit":[110],"operations.":[111],"Finally,":[112],"image":[115,150,158,168],"labeled":[116],"with":[117,206],"defects,":[118],"selective":[120],"search":[121],"non-maximum":[123],"algorithms":[124],"implemented":[126],"help":[128],"locate":[129],"coordinates":[131],"of":[132],"defects.":[133],"Experiments":[134],"show":[135],"that":[136,196],"BNN":[138,163,173,200],"model":[139],"on":[140],"can":[142,165,178,201,211],"achieve":[143],"97.9%":[144],"accuracy":[145,208],"in":[146,181,191],"identifying":[147],"whether":[148],"defective":[152],"defect-free.":[154],"As":[155],"classification":[159],"speed,":[160],"FPGA-based":[162,199],"module":[164],"process":[166],"one":[167],"within":[169],"0.5":[170],"s.":[171],"The":[172],"design":[174],"modularized":[176],"be":[179],"duplicated":[180],"parallel":[182],"fully":[184],"utilize":[185],"logic":[186],"gates":[187],"memory":[189],"resources":[190],"FPGAs.":[192],"It":[193],"clear":[195],"inspection":[205],"high":[207],"easily":[212],"scale":[213],"up":[214],"larger":[216],"implementations.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
