{"id":"https://openalex.org/W4386214823","doi":"https://doi.org/10.1109/iolts59296.2023.10224882","title":"Evaluation and Mitigation of Faults Affecting Swin Transformers","display_name":"Evaluation and Mitigation of Faults Affecting Swin Transformers","publication_year":2023,"publication_date":"2023-07-03","ids":{"openalex":"https://openalex.org/W4386214823","doi":"https://doi.org/10.1109/iolts59296.2023.10224882"},"language":"en","primary_location":{"id":"doi:10.1109/iolts59296.2023.10224882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iolts59296.2023.10224882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 29th International Symposium on On-Line Testing and Robust System Design (IOLTS)","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/A5011222292","display_name":"G. Gavarini","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"G. Gavarini","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy","Politecnico di Torino, DAUIN, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Politecnico di Torino, DAUIN, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083953105","display_name":"Annachiara Ruospo","orcid":"https://orcid.org/0000-0003-2040-9762"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"A. Ruospo","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy","Politecnico di Torino, DAUIN, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Politecnico di Torino, DAUIN, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009336869","display_name":"Ernesto S\u00e1nchez","orcid":"https://orcid.org/0000-0002-7042-295X"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"E. Sanchez","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy","Politecnico di Torino, DAUIN, Torino, Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]},{"raw_affiliation_string":"Politecnico di Torino, DAUIN, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011222292"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.6983,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75605921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9990000128746033,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7399883270263672},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.718947172164917},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6989444494247437},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6270321011543274},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5813207626342773},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5012302398681641},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4794436991214752},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.38851606845855713},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3795674741268158},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3789029121398926},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.20910969376564026},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17313140630722046},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.15896844863891602},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08774709701538086}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7399883270263672},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.718947172164917},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6989444494247437},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6270321011543274},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5813207626342773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5012302398681641},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4794436991214752},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.38851606845855713},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3795674741268158},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3789029121398926},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.20910969376564026},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17313140630722046},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.15896844863891602},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08774709701538086},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iolts59296.2023.10224882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iolts59296.2023.10224882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 29th International Symposium on On-Line Testing and Robust System Design (IOLTS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2748528844","https://openalex.org/W2901848761","https://openalex.org/W2943759410","https://openalex.org/W3036979375","https://openalex.org/W3138516171","https://openalex.org/W3187862527","https://openalex.org/W4283781063","https://openalex.org/W4297337482","https://openalex.org/W4310475705","https://openalex.org/W4312356560","https://openalex.org/W4321593286","https://openalex.org/W4379115996","https://openalex.org/W4384026303","https://openalex.org/W4385245566","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W4384112194","https://openalex.org/W2783354812","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W4308259661","https://openalex.org/W1969901537","https://openalex.org/W2376202349"],"abstract_inverted_index":{"In":[0,101],"the":[1,12,20,47,55,63,79,84,95,132,144,161,166,170,173,182,190,205],"last":[2],"decade,":[3],"a":[4,75,127,135,156,197,212],"huge":[5],"effort":[6],"has":[7],"been":[8],"spent":[9],"on":[10,160,165,169,180],"assessing":[11],"reliability":[13,76],"of":[14,57,69,78,83,134,172,184,199,214],"Convolutional":[15],"Neural":[16,31],"networks":[17],"(CNNs),":[18],"probably":[19],"most":[21,85],"popular":[22],"architecture":[23,53],"for":[24,41,89,143,202],"image":[25],"classification":[26],"tasks.":[27],"However,":[28],"modern":[29],"Deep":[30],"Networks":[32],"(DNNs)":[33],"are":[34,44,111],"rapidly":[35],"overtaking":[36],"CNNs,":[37,109,138],"as":[38,59,141],"state-of-the-art":[39],"results":[40,96],"many":[42],"tasks":[43],"achieved":[45],"with":[46],"Transformers,":[48],"innovative":[49],"DNN":[50,87],"models.":[51],"Transformers'":[52],"introduces":[54],"concept":[56],"attention":[58],"an":[60],"alternative":[61,147],"to":[62,73,108,113,130,154],"classical":[64],"convolution":[65],"operation.":[66],"The":[67,146],"aim":[68],"this":[70,103,151,208],"work":[71,152],"is":[72,122,139,153],"propose":[74],"analysis":[77],"Swin":[80],"Transformer,":[81],"one":[82],"accurate":[86],"used":[88],"Image":[90],"Classification,":[91],"that":[92,188],"greatly":[93],"improves":[94],"obtained":[97],"by":[98,150,196,211],"traditional":[99],"CNNs.":[100],"particular,":[102],"paper":[104],"shows":[105],"that,":[106,179],"similar":[107],"Transformers":[110],"susceptible":[112],"single":[114],"faults":[115,186,203],"affecting":[116,193,204],"weights":[117,207],"and":[118,168],"neurons.":[119],"Furthermore,":[120],"it":[121],"shown":[123],"how":[124],"output":[125],"ranging,":[126],"well-known":[128],"technique":[129],"reduce":[131],"impact":[133],"fault":[136],"in":[137],"not":[140,158],"effective":[142],"Transformer.":[145],"solution":[148],"proposed":[149],"introduce":[155],"ranging":[157],"only":[159],"output,":[162],"but":[163],"also":[164],"input":[167],"weight":[171],"fully":[174],"connected":[175],"layers.":[176],"Results":[177],"show":[178],"average,":[181],"number":[183],"critical":[185],"(i.e.,":[187],"modify":[189],"network's":[191,206],"output)":[192],"neurons":[194],"decreases":[195,210],"factor":[198,213],"1.91,":[200],"while":[201],"value":[209],"<tex":[215],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[216],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$1\\cdot":[217],"10^{5}$</tex>":[218],".":[219]},"counts_by_year":[{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
