{"id":"https://openalex.org/W4200451072","doi":"https://doi.org/10.1145/3487075.3487135","title":"Research on Mixed-Precision Quantization and Fault-Tolerant of Deep Neural Networks","display_name":"Research on Mixed-Precision Quantization and Fault-Tolerant of Deep Neural Networks","publication_year":2021,"publication_date":"2021-10-19","ids":{"openalex":"https://openalex.org/W4200451072","doi":"https://doi.org/10.1145/3487075.3487135"},"language":"en","primary_location":{"id":"doi:10.1145/3487075.3487135","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","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/A5055051446","display_name":"Zhaoxin Wang","orcid":"https://orcid.org/0009-0000-3226-8974"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhaoxin Wang","raw_affiliation_strings":["Department of Information Engineering, Capital Normal University, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Capital Normal University, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378697","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0003-3653-7013"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Department of Information Engineering, Capital Normal University, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Capital Normal University, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032971738","display_name":"Kun Qian","orcid":"https://orcid.org/0000-0002-1918-6453"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Qian","raw_affiliation_strings":["Department of Information Engineering, Capital Normal University, China"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Capital Normal University, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055051446"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20317554,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.7365000247955322,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.7365000247955322,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.711899995803833,"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/T14155","display_name":"Advanced Technology in Applications","score":0.6722000241279602,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/fault-tolerance","display_name":"Fault tolerance","score":0.816929817199707},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7917727828025818},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7316886782646179},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6064141988754272},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6046515107154846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4748000204563141},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44015058875083923},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3341159224510193},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.18185868859291077}],"concepts":[{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.816929817199707},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7917727828025818},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7316886782646179},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6064141988754272},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6046515107154846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4748000204563141},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44015058875083923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3341159224510193},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.18185868859291077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487075.3487135","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2173248099","https://openalex.org/W6775281461"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2055243143","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W4304166257","https://openalex.org/W4294635752","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W1963874442"],"abstract_inverted_index":{"As":[0],"deep":[1,52,68,93,103],"neural":[2,53,69,94,104,124],"networks":[3],"become":[4],"more":[5,7],"and":[6,18,118,170],"common":[8],"in":[9,29,46,140],"mission-critical":[10],"applications,":[11],"such":[12],"as":[13],"smart":[14],"medical":[15],"care,":[16],"drones,":[17],"autonomous":[19],"driving,":[20],"ensuring":[21],"their":[22],"reliable":[23],"operation":[24],"becomes":[25],"critical.":[26],"The":[27,126],"data":[28,113],"the":[30,47,51,57,64,67,81,86,92,102,110,120,123,129,134,137,144,152,161,171],"hardware":[31],"memory":[32],"is":[33,106],"susceptible":[34],"to":[35,38,43,78,97],"bit-flip":[36,117],"due":[37],"external":[39],"factors,":[40],"which":[41,108],"leads":[42],"a":[44,74],"decrease":[45],"inference":[48],"accuracy":[49,172],"of":[50,66,88,91,112,122,128,146,155,164],"network":[54,70,105,130],"deployed":[55],"on":[56],"hardware.":[58],"We":[59,72],"solve":[60],"this":[61,98,141],"problem":[62],"from":[63],"perspective":[65],"itself,":[71],"use":[73],"reinforcement":[75],"learning":[76],"algorithm":[77],"search":[79],"for":[80,85],"optimal":[82],"bit":[83,99],"width":[84,100],"weights":[87],"each":[89],"layer":[90],"network.":[95,125],"According":[96],"strategy,":[101],"quantified,":[107],"maximizes":[109],"limitation":[111],"fluctuations":[114],"caused":[115],"by":[116,149,158,167],"improves":[119,143],"fault-tolerance":[121,127,145],"model":[131,148,157,166],"compared":[132],"with":[133],"original":[135],"model,":[136],"solution":[138],"proposed":[139],"paper":[142],"LeNet5":[147],"8.5x":[150],",":[151,160,169],"fault":[153,162],"tolerance":[154,163],"MobileNetV2":[156],"15.6x":[159],"VGG16":[165],"14.5x":[168],"decreases":[173],"negligibly.":[174]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
