{"id":"https://openalex.org/W1661932126","doi":"https://doi.org/10.1109/isie.2015.7281599","title":"Inspecting surface mounted devices using k nearest neighbor and Multilayer Perceptron","display_name":"Inspecting surface mounted devices using k nearest neighbor and Multilayer Perceptron","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1661932126","doi":"https://doi.org/10.1109/isie.2015.7281599","mag":"1661932126"},"language":"en","primary_location":{"id":"doi:10.1109/isie.2015.7281599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie.2015.7281599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 24th International Symposium on Industrial Electronics (ISIE)","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/A5060963317","display_name":"Alexandre Reeberg de Mello","orcid":"https://orcid.org/0000-0003-3130-5328"},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alexandre R. de Mello","raw_affiliation_strings":["Department of Automation and Systems, Federal University of Santa Catarina, Florianopolis, Brazil","Dept. of Autom. & Syst., Federal Univ. of Santa Catarina, Florianopolis, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation and Systems, Federal University of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]},{"raw_affiliation_string":"Dept. of Autom. & Syst., Federal Univ. of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077339159","display_name":"Marcelo Ricardo Stemmer","orcid":"https://orcid.org/0000-0001-9386-805X"},"institutions":[{"id":"https://openalex.org/I4104125","display_name":"Universidade Federal de Santa Catarina","ror":"https://ror.org/041akq887","country_code":"BR","type":"education","lineage":["https://openalex.org/I4104125"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marcelo R. Stemmer","raw_affiliation_strings":["Department of Automation and Systems, Federal University of Santa Catarina, Florianopolis, Brazil","Dept. of Autom. & Syst., Federal Univ. of Santa Catarina, Florianopolis, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation and Systems, Federal University of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]},{"raw_affiliation_string":"Dept. of Autom. & Syst., Federal Univ. of Santa Catarina, Florianopolis, Brazil","institution_ids":["https://openalex.org/I4104125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7283,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8524434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"950","last_page":"955"},"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":1.0,"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":1.0,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9986000061035156,"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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/histogram","display_name":"Histogram","score":0.7835439443588257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7614580988883972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6912047266960144},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6733072996139526},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6141660213470459},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.6110685467720032},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.563123881816864},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5105706453323364},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.5088775157928467},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4989285469055176},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4766567349433899},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4727528989315033},{"id":"https://openalex.org/keywords/connected-component-labeling","display_name":"Connected-component labeling","score":0.43373504281044006},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.41400179266929626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1655920445919037},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.1421346366405487}],"concepts":[{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7835439443588257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7614580988883972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6912047266960144},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6733072996139526},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6141660213470459},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.6110685467720032},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.563123881816864},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5105706453323364},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.5088775157928467},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4989285469055176},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4766567349433899},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4727528989315033},{"id":"https://openalex.org/C58737948","wikidata":"https://www.wikidata.org/wiki/Q3136397","display_name":"Connected-component labeling","level":5,"score":0.43373504281044006},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.41400179266929626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1655920445919037},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.1421346366405487},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isie.2015.7281599","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isie.2015.7281599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 24th International Symposium on Industrial Electronics (ISIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.4399999976158142,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1508960934","https://openalex.org/W1520448186","https://openalex.org/W1680392829","https://openalex.org/W1966591781","https://openalex.org/W1984853662","https://openalex.org/W2004468037","https://openalex.org/W2005271384","https://openalex.org/W2048054084","https://openalex.org/W2065429801","https://openalex.org/W2109888465","https://openalex.org/W2114755081","https://openalex.org/W2133059825","https://openalex.org/W2145023731","https://openalex.org/W2147169507","https://openalex.org/W2152927648","https://openalex.org/W2161380045","https://openalex.org/W2170168007","https://openalex.org/W4244238212","https://openalex.org/W6637386731","https://openalex.org/W6684713405"],"related_works":["https://openalex.org/W1568952724","https://openalex.org/W2060330626","https://openalex.org/W2606438808","https://openalex.org/W1568383588","https://openalex.org/W2043403682","https://openalex.org/W2378232816","https://openalex.org/W1980767234","https://openalex.org/W2170080636","https://openalex.org/W2766329551","https://openalex.org/W2378792248"],"abstract_inverted_index":{"Automatic":[0],"inspection":[1,30,127],"of":[2,8,19,25,56,85,89],"electronic":[3],"components":[4],"during":[5],"the":[6,17,23,50,77,83,87,112,126,130,137],"production":[7],"printed":[9],"circuit":[10],"boards":[11],"is":[12,40],"a":[13,90,105,115],"way":[14],"to":[15,97,110],"ensure":[16],"quality":[18],"this":[20,43],"production,":[21],"reducing":[22],"cost":[24],"re-work.":[26],"An":[27],"automatic":[28],"optical":[29],"system":[31,128],"based":[32],"on":[33,48],"AI":[34],"techniques":[35,122],"for":[36],"surface":[37],"mounted":[38],"devices":[39],"proposed":[41],"in":[42,76,100,125],"work.":[44],"The":[45],"method":[46,107],"relies":[47],"extracting":[49],"contour":[51],"and":[52,68,102,108,133],"histogram":[53,69],"related":[54,72,93],"features":[55,73,94],"component":[57,113],"images,":[58],"using":[59,114],"Watershed":[60],"segmentation,":[61],"Canny":[62],"edge":[63],"detection,":[64],"border":[65],"following":[66],"algorithm":[67],"analysis.":[70],"Histogram":[71],"are":[74,95,134],"applied":[75],"k":[78],"nearest":[79],"neighbor":[80],"technique":[81],"with":[82,129],"goal":[84],"identifying":[86],"existence":[88],"component.":[91],"Contour":[92],"used":[96,124],"identify":[98],"changes":[99],"angle":[101],"position":[103],"by":[104],"comparison":[106],"also":[109],"classify":[111],"Multilayer":[116],"Perceptron":[117],"(MLP)":[118],"neural":[119],"network.":[120],"Both":[121],"were":[123],"chosen":[131],"features,":[132],"validated":[135],"through":[136],"10-fold":[138],"cross":[139],"validation":[140],"data":[141],"method.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}