{"id":"https://openalex.org/W4398131396","doi":"https://doi.org/10.1007/s10845-024-02377-4","title":"Sparse deep encoded features with enhanced sinogramic red deer optimization for fault inspection in wafer maps","display_name":"Sparse deep encoded features with enhanced sinogramic red deer optimization for fault inspection in wafer maps","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4398131396","doi":"https://doi.org/10.1007/s10845-024-02377-4"},"language":"en","primary_location":{"id":"doi:10.1007/s10845-024-02377-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02377-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02377-4.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02377-4.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080192151","display_name":"Doaa A. Altantawy","orcid":"https://orcid.org/0000-0001-6476-2934"},"institutions":[{"id":"https://openalex.org/I159247623","display_name":"Mansoura University","ror":"https://ror.org/01k8vtd75","country_code":"EG","type":"education","lineage":["https://openalex.org/I159247623"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Doaa A. Altantawy","raw_affiliation_strings":["Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 60 El-Gomhoria Street, Mansoura, Egypt"],"raw_orcid":"https://orcid.org/0000-0001-6476-2934","affiliations":[{"raw_affiliation_string":"Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 60 El-Gomhoria Street, Mansoura, Egypt","institution_ids":["https://openalex.org/I159247623"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103524335","display_name":"Mohamed Yakout","orcid":null},"institutions":[{"id":"https://openalex.org/I159247623","display_name":"Mansoura University","ror":"https://ror.org/01k8vtd75","country_code":"EG","type":"education","lineage":["https://openalex.org/I159247623"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mohamed A. Yakout","raw_affiliation_strings":["Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 60 El-Gomhoria Street, Mansoura, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, 60 El-Gomhoria Street, Mansoura, Egypt","institution_ids":["https://openalex.org/I159247623"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5080192151"],"corresponding_institution_ids":["https://openalex.org/I159247623"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.9101,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76381792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"36","issue":"5","first_page":"3359","last_page":"3397"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9907000064849854,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9887999892234802,"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/wafer","display_name":"Wafer","score":0.6622111201286316},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5506762862205505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399956107139587},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4864335060119629},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4420888423919678},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32570022344589233},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.26646149158477783},{"id":"https://openalex.org/keywords/nanotechnology","display_name":"Nanotechnology","score":0.17674750089645386},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.161958247423172},{"id":"https://openalex.org/keywords/seismology","display_name":"Seismology","score":0.0801229476928711}],"concepts":[{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.6622111201286316},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5506762862205505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399956107139587},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4864335060119629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4420888423919678},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32570022344589233},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.26646149158477783},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.17674750089645386},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.161958247423172},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0801229476928711}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10845-024-02377-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02377-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02377-4.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:joinma:v:36:y:2025:i:5:d:10.1007_s10845-024-02377-4","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s10845-024-02377-4","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10845-024-02377-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10845-024-02377-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10845-024-02377-4.pdf","source":{"id":"https://openalex.org/S161464388","display_name":"Journal of Intelligent Manufacturing","issn_l":"0956-5515","issn":["0956-5515","1572-8145"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Manufacturing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6399999856948853}],"awards":[],"funders":[{"id":"https://openalex.org/F4320325716","display_name":"Mansoura University","ror":"https://ror.org/01k8vtd75"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4398131396.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W2013927912","https://openalex.org/W2020286945","https://openalex.org/W2032099903","https://openalex.org/W2034243637","https://openalex.org/W2081054913","https://openalex.org/W2160679312","https://openalex.org/W2770073247","https://openalex.org/W2805484002","https://openalex.org/W2888261345","https://openalex.org/W2922187519","https://openalex.org/W2943898222","https://openalex.org/W2945987769","https://openalex.org/W3005244013","https://openalex.org/W3011016572","https://openalex.org/W3100777112","https://openalex.org/W3134482315","https://openalex.org/W3137061779","https://openalex.org/W3139531532","https://openalex.org/W3151307229","https://openalex.org/W3193550730","https://openalex.org/W3195021195","https://openalex.org/W3196631891","https://openalex.org/W3197201339","https://openalex.org/W3198927221","https://openalex.org/W3199285415","https://openalex.org/W3201304935","https://openalex.org/W3210425092","https://openalex.org/W3212904554","https://openalex.org/W4205129187","https://openalex.org/W4210493968","https://openalex.org/W4210680911","https://openalex.org/W4210686785","https://openalex.org/W4223475101","https://openalex.org/W4283373853","https://openalex.org/W4283387112","https://openalex.org/W4285798956","https://openalex.org/W4286687376","https://openalex.org/W4290716256","https://openalex.org/W4291281567","https://openalex.org/W4292722430","https://openalex.org/W4300962805","https://openalex.org/W4309709748","https://openalex.org/W4315782999","https://openalex.org/W4319304591","https://openalex.org/W4322704400","https://openalex.org/W4323545743","https://openalex.org/W4376456922"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Abstract":[0],"Due":[1],"to":[2,119,138,157,161,176,199,212,215,243,288],"the":[3,8,35,41,54,69,72,84,140,145,158,200,205,253,257,263,291],"complexity":[4],"and":[5,37,80,103,309,313],"dynamics":[6],"of":[7,78,86,144,185,252,256,316],"semiconductor":[9],"manufacturing":[10],"processes,":[11],"wafer":[12,30,115,165,186,202,259,283],"bin":[13],"maps":[14,31,160,166,187,209],"(WBM)":[15],"present":[16],"various":[17,22],"defect":[18,26,42],"patterns":[19],"caused":[20],"by":[21,167],"process":[23,36],"faults.":[24],"The":[25,182,237,272,303],"type":[27],"detection":[28,118],"on":[29,281],"provides":[32],"information":[33],"about":[34],"equipment":[38],"in":[39,52,93,172,195],"which":[40,64],"occurred.":[43],"Recently,":[44],"automatic":[45],"inspection":[46,274],"has":[47],"played":[48],"a":[49,75,109,127,135,169,178,226,233,266],"vital":[50],"role":[51],"meeting":[53],"high-throughput":[55],"demand,":[56],"especially":[57],"with":[58,192,232,298],"deep":[59,112],"convolutional":[60,129],"neural":[61],"networks":[62],"(DCNN)":[63],"shows":[65],"promising":[66],"efficiency.":[67],"At":[68],"same":[70],"time,":[71],"need":[73],"for":[74,114,148,262,311],"large":[76],"amount":[77],"labeled":[79],"balanced":[81],"datasets":[82],"limits":[83],"performance":[85,296],"such":[87],"approaches.":[88],"In":[89,106],"addition,":[90],"complex":[91],"DCNN":[92],"recognition":[94],"tasks":[95],"can":[96],"provide":[97],"redundant":[98],"features":[99,191],"that":[100],"cause":[101],"overfitting":[102],"reduce":[104],"interpretability.":[105],"this":[107],"paper,":[108],"new":[110,128,227,234],"hybrid":[111],"model":[113,137,269,275,293],"map":[116,284],"fault":[117],"get":[120,162],"over":[121],"these":[122],"challenges":[123],"is":[124,132,155,241,270,276],"proposed.":[125],"Firstly,":[126],"autoencoder":[130,180],"(CAE)":[131],"employed":[133],"as":[134],"synthetization":[136],"fix":[139],"high":[141],"imbalance":[142],"problem":[143],"dataset.":[146],"Secondly,":[147],"efficient":[149],"dimensionality":[150],"reduction,":[151],"an":[152,173],"embedding":[153,184],"procedure":[154],"applied":[156],"synthesized":[159],"sparse":[163,183,208],"encoded":[164,207],"reinforcing":[168],"sparsity":[170],"regularization":[171],"encoder-decoder":[174],"network":[175],"form":[177],"sparsity-boosted":[179],"(SBAE).":[181],"guarantees":[188],"more":[189],"discriminative":[190],"50%":[193],"reduction":[194,223],"spatial":[196],"size":[197,255],"compared":[198],"original":[201],"maps.":[203,260],"Then,":[204],"2D":[206,258],"are":[210,307],"converted":[211],"1D":[213,246,300],"sinograms":[214],"be":[216],"fed":[217],"later":[218],"into":[219],"another":[220],"aggressive":[221],"feature":[222,239,247,301],"stage":[224],"using":[225],"modified":[228],"red":[229],"deer":[230],"algorithm":[231],"tinkering":[235],"strategy.":[236],"resultant":[238],"pool":[240],"reduced":[242],"~":[244,250],"25":[245],"bases,":[248],"i.e.,":[249],"1.5%":[251],"initial":[254],"Finally,":[261],"prediction":[264],"stage,":[265],"simple":[267],"1DCNN":[268],"introduced.":[271],"proposed":[273,292],"tested":[277],"via":[278],"different":[279],"experiments":[280],"real-world":[282],"dataset":[285],"(WM-811K).":[286],"Compared":[287],"state-of-the-art":[289],"techniques,":[290],"outperforms":[294],"their":[295],"even":[297],"small-sized":[299],"pool.":[302],"average":[304],"testing":[305],"accuracy":[306],"98.77%":[308],"98.8%":[310],"9":[312],"8":[314],"types":[315],"faults,":[317],"respectively.":[318]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
