{"id":"https://openalex.org/W4409536512","doi":"https://doi.org/10.1109/lats65346.2025.10963935","title":"DOC: Detection of On-Line Failures in CNNs","display_name":"DOC: Detection of On-Line Failures in CNNs","publication_year":2025,"publication_date":"2025-03-11","ids":{"openalex":"https://openalex.org/W4409536512","doi":"https://doi.org/10.1109/lats65346.2025.10963935"},"language":"en","primary_location":{"id":"doi:10.1109/lats65346.2025.10963935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats65346.2025.10963935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 26th Latin American Test Symposium (LATS)","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/A5064581320","display_name":"V. Turco","orcid":"https://orcid.org/0009-0001-0754-8189"},"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":"V. Turco","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047075336","display_name":"Nicol\u00f2 Bellarmino","orcid":"https://orcid.org/0000-0001-5887-2598"},"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":"N. Bellarmino","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy"],"affiliations":[{"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"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089672314","display_name":"Riccardo Cantoro","orcid":"https://orcid.org/0000-0002-1745-5293"},"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":"R. Cantoro","raw_affiliation_strings":["Politecnico di Torino, DAUIN,Torino,Italy"],"affiliations":[{"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"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, DAUIN,Torino,Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5064581320"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03827701,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9889000058174133,"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":0.9889000058174133,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9266999959945679,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.921999990940094,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.6132826805114746},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.5088213086128235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36316460371017456},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3539385497570038},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05926746129989624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6132826805114746},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.5088213086128235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36316460371017456},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3539385497570038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05926746129989624},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lats65346.2025.10963935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lats65346.2025.10963935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 26th Latin American Test Symposium (LATS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2911496292","https://openalex.org/W3182269065","https://openalex.org/W4211189626","https://openalex.org/W4282966318","https://openalex.org/W4309675334","https://openalex.org/W4319879374","https://openalex.org/W4379115996","https://openalex.org/W4384026292","https://openalex.org/W4388821019","https://openalex.org/W4396531566","https://openalex.org/W4399510124"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0,73],"integration":[1],"of":[2,19,25,30,90,120,149,164],"Artificial":[3],"Intelligence":[4],"(AI)":[5],"in":[6,53,166],"safety-critical":[7,167],"systems":[8],"raises":[9],"concerns":[10],"about":[11],"reliability,":[12],"particularly":[13],"due":[14],"to":[15,146],"the":[16,23,54,88,95,134,141,162],"inherent":[17],"uncertainty":[18],"AI":[20],"algorithms":[21,44],"and":[22],"complexity":[24],"modern":[26],"hardware,":[27],"compromising":[28],"billion":[29],"transistors.":[31],"Existing":[32],"solutions,":[33],"such":[34],"as":[35,81],"Algorithm-Based":[36],"Fault":[37],"Tolerance":[38],"often":[39],"focus":[40],"on":[41,87,133],"running":[42],"detection":[43,55,63,125],"after":[45],"every":[46],"inference,":[47],"introducing":[48],"a":[49,60,85,91,103,138],"not":[50],"negligible":[51],"overhead":[52],"phase.":[56],"This":[57,157],"paper":[58],"introduces":[59],"two-phase":[61],"fault":[62],"technique":[64],"for":[65,128],"Convolutional":[66],"Neural":[67],"Networks":[68],"(CNNs)":[69],"with":[70,137],"floating-point":[71,92],"precision.":[72],"first":[74],"phase":[75],"identifies":[76],"easily":[77],"detectable":[78],"faults":[79,116],"(such":[80],"those":[82],"stemming":[83],"from":[84],"bit-flip":[86],"30th":[89],"representation),":[93],"while":[94,152],"second":[96],"one":[97],"targets":[98],"hard-to-detect":[99],"critical":[100,122,150],"faults\u2014those":[101],"producing":[102],"wrong":[104],"prediction":[105],"but":[106],"having":[107],"no":[108],"visible":[109],"effect":[110],"during":[111],"faults'":[112],"propagation.":[113],"Although":[114],"these":[115],"constitute":[117],"only":[118],"1.4%":[119],"all":[121],"faults,":[123],"their":[124],"is":[126],"crucial":[127],"ensuring":[129],"system":[130],"reliability.":[131],"Validated":[132],"CIFAR-10":[135],"dataset":[136],"ResNet-20":[139],"model,":[140],"proposed":[142],"method":[143],"achieves":[144],"up":[145],"99.67%":[147],"coverage":[148],"inferences":[151],"maintaining":[153],"moderate":[154],"computational":[155],"overhead.":[156],"lightweight,":[158],"real-time":[159],"solution":[160],"enhances":[161],"robustness":[163],"CNNs":[165],"applications.":[168]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}