{"id":"https://openalex.org/W3000421178","doi":"https://doi.org/10.1109/taai48200.2019.8959827","title":"Ball-Grid-Array Chip Defects Detection and Classification Using Patch-based Modified YOLOv3","display_name":"Ball-Grid-Array Chip Defects Detection and Classification Using Patch-based Modified YOLOv3","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3000421178","doi":"https://doi.org/10.1109/taai48200.2019.8959827","mag":"3000421178"},"language":"en","primary_location":{"id":"doi:10.1109/taai48200.2019.8959827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taai48200.2019.8959827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Technologies and Applications of Arti\ufb01cial Intelligence (TAAI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5090735162","display_name":"Phong-Phu Le","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Phong-Phu Le","raw_affiliation_strings":["Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101880209","display_name":"Shu\u2010Mei Guo","orcid":"https://orcid.org/0000-0001-6807-8427"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shu-Mei Guo","raw_affiliation_strings":["Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113478139","display_name":"Ju-Chin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I192168892","display_name":"National University of Kaohsiung","ror":"https://ror.org/013zjb662","country_code":"TW","type":"education","lineage":["https://openalex.org/I192168892"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ju-Chin Chen","raw_affiliation_strings":["Dept. of Computer Science and Information Engineering, National Kaohisung University of Science and Technology, Kaohsiung, Taiwan (R.O.C)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Information Engineering, National Kaohisung University of Science and Technology, Kaohsiung, Taiwan (R.O.C)","institution_ids":["https://openalex.org/I192168892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045190381","display_name":"Jenn-Jier James Lien","orcid":"https://orcid.org/0000-0003-3944-7523"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jenn-Jier James Lien","raw_affiliation_strings":["Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C)","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8166,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.72016558,"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":"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9968000054359436,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9879000186920166,"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/ball-grid-array","display_name":"Ball grid array","score":0.8721174001693726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7288037538528442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6640866994857788},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6604814529418945},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.605886697769165},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5256801247596741},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4859665632247925},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47982263565063477},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.47658202052116394},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4503145217895508},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41276246309280396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09563612937927246}],"concepts":[{"id":"https://openalex.org/C94709252","wikidata":"https://www.wikidata.org/wiki/Q570628","display_name":"Ball grid array","level":3,"score":0.8721174001693726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7288037538528442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6640866994857788},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6604814529418945},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.605886697769165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5256801247596741},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4859665632247925},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47982263565063477},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.47658202052116394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4503145217895508},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41276246309280396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09563612937927246},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C50296614","wikidata":"https://www.wikidata.org/wiki/Q211387","display_name":"Soldering","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taai48200.2019.8959827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taai48200.2019.8959827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Technologies and Applications of Arti\ufb01cial Intelligence (TAAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2109255472","https://openalex.org/W2194775991","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2796347433","https://openalex.org/W2884068670","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W6639102338","https://openalex.org/W6731892127","https://openalex.org/W6735463952","https://openalex.org/W6750227808","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W1975509756","https://openalex.org/W2122379732","https://openalex.org/W1916213107","https://openalex.org/W4391482815","https://openalex.org/W2359189194","https://openalex.org/W567677580","https://openalex.org/W2321214384","https://openalex.org/W2117825347","https://openalex.org/W2075432981","https://openalex.org/W3022507253"],"abstract_inverted_index":{"The":[0],"tiny":[1],"size":[2],"of":[3,39,63,76,86,111,120,129,135,178,193,200,206],"defects":[4,90],"and":[5,35,71,78,88,125,168,202],"the":[6,10,18,25,32,64,84,109,118,123,127,133,162,170,176,186],"noise":[7],"information":[8,121],"in":[9,24,74],"Ball-Grid-Array":[11],"(BGA)":[12],"Chip":[13,93,140,153,180],"images":[14],"have":[15],"been":[16],"challenging":[17],"image-processing":[19],"based":[20],"visual":[21],"inspection":[22],"systems":[23],"Integrated":[26],"Circuit":[27],"(IC)":[28],"manufacturing":[29],"industry.":[30],"Moreover,":[31],"gradient":[33],"vanishing":[34],"high":[36],"time-consuming":[37],"problems":[38],"deep":[40],"neural":[41],"network":[42,124],"models":[43],"are":[44,96,105,158],"a":[45,60,67,149,174],"big":[46],"obstacle":[47],"for":[48],"its":[49,79],"application":[50,80,134],"to":[51,81,107,166],"solve":[52],"industrial":[53],"projects.":[54],"This":[55],"paper":[56],"focuses":[57],"on":[58,91,100],"proposing":[59],"modified":[61,163],"version":[62],"YOLOv3":[65,102,164],"model,":[66],"leading":[68],"object":[69],"detection":[70],"classification":[72],"method":[73],"terms":[75],"speed;":[77],"deal":[82],"with":[83,185],"problem":[85,128,177],"detecting":[87],"classifying":[89],"BGA":[92,139,152,179],"Images.":[94],"There":[95],"five":[97],"modifications":[98],"constructed":[99],"(4)":[101],"architecture":[103],"that":[104],"aimed":[106],"enhance":[108],"ability":[110],"feature":[112],"extraction":[113],"towards":[114],"small":[115],"objects,":[116],"strengthen":[117],"flow":[119],"inside":[122],"eliminate":[126],"redundant":[130],"information.":[131],"With":[132],"this":[136],"model":[137,165],"into":[138,161],"Defects":[141,181],"estimation,":[142],"49":[143],"patches":[144],"(320x320":[145],"pixels),":[146,157],"extracted":[147],"from":[148],"single":[150],"high-resolution":[151],"image":[154],"(1,":[155],"450x1,450":[156],"continuously":[159],"fed":[160],"detect":[167],"classify":[169],"inner":[171],"defects.":[172],"As":[173],"result,":[175],"estimation":[182],"is":[183],"solved":[184],"highest":[187],"performance":[188],"achieves":[189],"an":[190,203],"average":[191,204],"precision":[192],"86%":[194],"at":[195],"IoU":[196],"(Intersection":[197],"over":[198],"Union)":[199],"0.75":[201],"recall":[205],"99%.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}