{"id":"https://openalex.org/W3046108700","doi":"https://doi.org/10.3906/elk-1910-135","title":"Detection of BGA solder defects from X-ray images using deep neural network","display_name":"Detection of BGA solder defects from X-ray images using deep neural network","publication_year":2020,"publication_date":"2020-03-10","ids":{"openalex":"https://openalex.org/W3046108700","doi":"https://doi.org/10.3906/elk-1910-135","mag":"3046108700"},"language":"en","primary_location":{"id":"doi:10.3906/elk-1910-135","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-1910-135","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1305&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING &amp; COMPUTER SCIENCES","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1305&context=elektrik","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5098158045","display_name":"Ceren T\u00dcRER AKDEN\u0130Z","orcid":"https://orcid.org/0000-0002-9617-4069"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ceren T\u00dcRER AKDEN\u0130Z","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-9617-4069","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072989626","display_name":"Z\u00fcmray Dokur","orcid":"https://orcid.org/0000-0001-7660-3236"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Z\u00fcmray DOKUR","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-7660-3236","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5006261253","display_name":"Tamer \u00d6lmez","orcid":"https://orcid.org/0000-0001-6124-2394"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tamer \u00d6LMEZ","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-6124-2394","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6244,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.68072673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"28","issue":"4","first_page":"2020","last_page":"2029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10460","display_name":"Electronic Packaging and Soldering Technologies","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10460","display_name":"Electronic Packaging and Soldering Technologies","score":0.9986000061035156,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9973000288009644,"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":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ball-grid-array","display_name":"Ball grid array","score":0.9561524391174316},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.736060380935669},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.677674412727356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6630438566207886},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6013299822807312},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47778066992759705},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.44592511653900146},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.43412789702415466},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4326012432575226},{"id":"https://openalex.org/keywords/soldering","display_name":"Soldering","score":0.4301997423171997},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.429311603307724},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.41167041659355164},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3788517713546753},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29513466358184814},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.23804232478141785}],"concepts":[{"id":"https://openalex.org/C94709252","wikidata":"https://www.wikidata.org/wiki/Q570628","display_name":"Ball grid array","level":3,"score":0.9561524391174316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.736060380935669},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.677674412727356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6630438566207886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6013299822807312},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47778066992759705},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.44592511653900146},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.43412789702415466},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4326012432575226},{"id":"https://openalex.org/C50296614","wikidata":"https://www.wikidata.org/wiki/Q211387","display_name":"Soldering","level":2,"score":0.4301997423171997},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.429311603307724},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.41167041659355164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3788517713546753},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29513466358184814},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.23804232478141785},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3906/elk-1910-135","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-1910-135","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1305&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING &amp; COMPUTER SCIENCES","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3906/elk-1910-135","is_oa":true,"landing_page_url":"https://doi.org/10.3906/elk-1910-135","pdf_url":"https://journals.tubitak.gov.tr/cgi/viewcontent.cgi?article=1305&context=elektrik","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING &amp; COMPUTER SCIENCES","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3046108700.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1975509756","https://openalex.org/W2380335578","https://openalex.org/W2079719989","https://openalex.org/W2367693714","https://openalex.org/W4295036922","https://openalex.org/W2365278150","https://openalex.org/W2313417573","https://openalex.org/W2361190668","https://openalex.org/W2316528830","https://openalex.org/W2360913040"],"abstract_inverted_index":{"In":[0,30,48],"the":[1,14,62,80,99,102,107,125,128,164,168,174,179,183,195,202],"literature":[2],"it":[3,33],"is":[4,58,144,161,171,192],"observed":[5],"that":[6,37],"complex":[7],"image":[8],"processing":[9],"operations":[10],"are":[11,41,109,118],"used":[12,140],"in":[13,45,111,141,182],"classification":[15,25,46,196],"of":[16,84,87,98,101,106,127,146,158,190,197],"Ball":[17],"Grid":[18],"Array":[19],"(BGA)":[20],"X-ray":[21,64,116,199],"images,":[22],"however":[23],"high":[24,187],"results":[26],"were":[27],"not":[28],"achieved.":[29],"recent":[31],"years,":[32],"has":[34],"been":[35],"shown":[36],"deep":[38,53],"learning":[39],"methods":[40,181],"very":[42,186],"successful":[43],"especially":[44],"problems.":[47],"this":[49,142],"study,":[50],"a":[51,75,112,185],"new":[52],"neural":[54],"network":[55,82,103,108],"(DNN)":[56],"model":[57,69],"proposed":[59,67,81,203],"to":[60,124],"classify":[61],"BGA":[63,115,198],"images.":[65],"The":[66,138],"DNN":[68],"contains":[70],"feature":[71],"extractor":[72],"layers":[73,88,91],"and":[74,92,104,135,150,167],"minimum":[76],"distance":[77],"classifier.":[78],"Since":[79],"consists":[83],"less":[85],"number":[86],"(4":[89],"convolution":[90],"1":[93],"fully":[94],"connected":[95],"layer),":[96],"determination":[97],"hyper-parameters":[100],"training":[105,165],"accomplished":[110],"short":[113],"time.":[114],"images":[117,152,200],"categorized":[119],"into":[120],"4":[121],"classes":[122],"according":[123],"conditions":[126],"solder":[129],"joints:":[130],"normal,":[131],"short-circuit,":[132],"bonding":[133],"defect":[134],"void":[136],"defect.":[137],"dataset":[139],"study":[143],"comprised":[145],"67,":[147],"76,":[148],"53":[149],"76":[151],"for":[153,163,173,194],"these":[154],"classes,":[155],"respectively.":[156],"80%":[157],"all":[159],"data":[160],"allocated":[162,172],"set":[166],"remaining":[169],"20%":[170],"test":[175],"set.":[176],"Compared":[177],"with":[178,201],"existing":[180],"literature,":[184],"success":[188],"rate":[189],"97%":[191],"achieved":[193],"method.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
