{"id":"https://openalex.org/W4416649598","doi":"https://doi.org/10.1109/tase.2025.3635887","title":"Unpaired Image Denoising and Fusion With Adaptive Multi-Branch Task UNet for Semiconductor Packaging Defect Recognition","display_name":"Unpaired Image Denoising and Fusion With Adaptive Multi-Branch Task UNet for Semiconductor Packaging Defect Recognition","publication_year":2025,"publication_date":"2025-11-25","ids":{"openalex":"https://openalex.org/W4416649598","doi":"https://doi.org/10.1109/tase.2025.3635887"},"language":null,"primary_location":{"id":"doi:10.1109/tase.2025.3635887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3635887","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-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/A5104274492","display_name":"T. C. Hsieh","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":true,"raw_author_name":"Tsung-Ta Hsieh","raw_affiliation_strings":["Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021866378","display_name":"Chia\u2010Yen Lee","orcid":"https://orcid.org/0000-0002-2928-3337"},"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":"Chia-Yen Lee","raw_affiliation_strings":["Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042982003","display_name":"Yu-Hsin Hung","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Hsin Hung","raw_affiliation_strings":["Department of Information Management, National Taiwan University, Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Information Management, National Taiwan University, Taipei, Taiwan","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051073438","display_name":"Po-Cheng Shen","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":"Po-Cheng Shen","raw_affiliation_strings":["Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048218061","display_name":"Taho Yang","orcid":"https://orcid.org/0000-0002-6317-4636"},"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":"Taho Yang","raw_affiliation_strings":["Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5104274492"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.50950297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"1650","last_page":"1665"},"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":0.585099995136261,"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":0.585099995136261,"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":0.09200000017881393,"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/T11527","display_name":"3D IC and TSV technologies","score":0.04820000007748604,"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/noise-reduction","display_name":"Noise reduction","score":0.6682999730110168},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6212000250816345},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6032000184059143},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5514000058174133},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5038999915122986},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4846000075340271},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44359999895095825},{"id":"https://openalex.org/keywords/integrated-circuit-packaging","display_name":"Integrated circuit packaging","score":0.42809998989105225},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.41499999165534973}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7621999979019165},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6682999730110168},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6212000250816345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6122999787330627},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6032000184059143},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5662000179290771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5514000058174133},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5038999915122986},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44359999895095825},{"id":"https://openalex.org/C186260285","wikidata":"https://www.wikidata.org/wiki/Q759494","display_name":"Integrated circuit packaging","level":3,"score":0.42809998989105225},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.41499999165534973},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.3937000036239624},{"id":"https://openalex.org/C70000540","wikidata":"https://www.wikidata.org/wiki/Q26468","display_name":"Moir\u00e9 pattern","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.33820000290870667},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.334199994802475},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.32330000400543213},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3068999946117401},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3003000020980835},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.28700000047683716},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27129998803138733},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2624000012874603},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.2603999972343445},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2025.3635887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3635887","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1505855572","https://openalex.org/W2899279931","https://openalex.org/W2956015785","https://openalex.org/W2963351448","https://openalex.org/W2963430933","https://openalex.org/W2963677766","https://openalex.org/W2964098128","https://openalex.org/W2983315964","https://openalex.org/W2987138151","https://openalex.org/W2997053073","https://openalex.org/W3017124793","https://openalex.org/W3026852900","https://openalex.org/W3034922746","https://openalex.org/W3095592139","https://openalex.org/W3099863631","https://openalex.org/W3141797743","https://openalex.org/W3176624929","https://openalex.org/W3207092584","https://openalex.org/W3207181952","https://openalex.org/W4205620295","https://openalex.org/W4206290629","https://openalex.org/W4225538054","https://openalex.org/W4225672218","https://openalex.org/W4289132173","https://openalex.org/W4289752563","https://openalex.org/W4294775232","https://openalex.org/W4300472483","https://openalex.org/W4312209940","https://openalex.org/W4312399981","https://openalex.org/W4321458273","https://openalex.org/W4376869102","https://openalex.org/W4379054153","https://openalex.org/W4385810890","https://openalex.org/W4386121018","https://openalex.org/W4391454560","https://openalex.org/W4391505996","https://openalex.org/W4394928976","https://openalex.org/W4408027916","https://openalex.org/W4408449236","https://openalex.org/W4409560761"],"related_works":[],"abstract_inverted_index":{"In":[0],"advanced":[1],"semiconductor":[2,97],"packaging,":[3],"products":[4],"often":[5],"exhibit":[6],"high":[7],"unit":[8],"cost,":[9],"complex":[10],"structures,":[11],"and":[12,51,121,138,146],"stringent":[13],"precision":[14],"requirements.":[15],"Inspection":[16],"systems":[17],"such":[18,118],"as":[19,119,131],"Scanning":[20],"Acoustic":[21],"Microscopy":[22],"(SAM)":[23],"are":[24,41],"employed":[25],"to":[26,43,101,149],"detect":[27],"internal":[28],"defects,":[29],"particularly":[30],"within":[31],"the":[32,103,134],"Epoxy":[33],"Molding":[34],"Compound":[35],"(EMC)":[36],"layer.":[37],"However,":[38],"ultrasound":[39],"images":[40],"susceptible":[42],"various":[44],"noise":[45,91],"sources":[46],"that":[47,126],"degrade":[48],"image":[49,60,141],"quality":[50],"hinder":[52],"defect":[53],"identification.":[54],"This":[55],"study":[56,95],"proposes":[57],"a":[58,70,74],"self-supervised":[59],"denoising":[61],"framework":[62],"called":[63],"Multi-Branch":[64],"Task":[65],"U-Net":[66,71],"(MBT-UNet),":[67],"which":[68],"is":[69,99,147],"backbone":[72],"with":[73,109],"multi-branch":[75],"decoder.":[76],"The":[77,123],"model":[78],"enables":[79],"multi-task":[80],"learning":[81,116],"without":[82,155],"requiring":[83],"paired":[84,114,156],"clean-noisy":[85],"data":[86],"or":[87],"prior":[88],"knowledge":[89],"of":[90,96],"characteristics.":[92],"An":[93],"empirical":[94],"packaging":[98],"conducted":[100],"validate":[102],"proposed":[104],"MBT-UNet":[105,127],"by":[106,133],"comparing":[107],"it":[108],"several":[110],"benchmark":[111],"methods":[112],"(e.g.,":[113],"supervised":[115,150],"approaches":[117],"SC-UNet":[120],"RIDNet).":[122],"results":[124],"show":[125],"achieves":[128],"competitive":[129],"performance,":[130],"evaluated":[132],"feature":[135],"similarity":[136,143],"(FSIM)":[137],"learned":[139],"perceptual":[140],"patch":[142],"(LPIPS)":[144],"metrics,":[145],"comparable":[148],"models":[151],"despite":[152],"being":[153],"trained":[154],"data.":[157]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-25T00:00:00"}
