{"id":"https://openalex.org/W4283452163","doi":"https://doi.org/10.1109/ismvl52857.2022.00035","title":"Fast Interface with Ensemble Ternary Neural Network","display_name":"Fast Interface with Ensemble Ternary Neural Network","publication_year":2022,"publication_date":"2022-05-01","ids":{"openalex":"https://openalex.org/W4283452163","doi":"https://doi.org/10.1109/ismvl52857.2022.00035"},"language":"en","primary_location":{"id":"doi:10.1109/ismvl52857.2022.00035","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismvl52857.2022.00035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 52nd International Symposium on Multiple-Valued Logic (ISMVL)","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/A5030076284","display_name":"Ryota Kayanoma","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ryota Kayanoma","raw_affiliation_strings":["Tokyo Institute of Technology,Japan","Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology,Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070734898","display_name":"Hiroki Nakahara","orcid":"https://orcid.org/0000-0002-5701-7466"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Nakahara","raw_affiliation_strings":["Tokyo Institute of Technology,Japan","Tokyo Institute of Technology, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology,Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"Tokyo Institute of Technology, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030076284"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":0.1006,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.35991428,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"182","last_page":"187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9991000294685364,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9976000189781189,"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/computer-science","display_name":"Computer science","score":0.7560039758682251},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.7372363209724426},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7276002168655396},{"id":"https://openalex.org/keywords/content-addressable-memory","display_name":"Content-addressable memory","score":0.6386024355888367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5177004337310791},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.48481956124305725},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.46288061141967773},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4479144811630249},{"id":"https://openalex.org/keywords/ternary-operation","display_name":"Ternary operation","score":0.43783196806907654},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38061708211898804},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3432180881500244},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.33222496509552},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.29298511147499084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560039758682251},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.7372363209724426},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7276002168655396},{"id":"https://openalex.org/C53442348","wikidata":"https://www.wikidata.org/wiki/Q745101","display_name":"Content-addressable memory","level":3,"score":0.6386024355888367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177004337310791},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.48481956124305725},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.46288061141967773},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4479144811630249},{"id":"https://openalex.org/C64452783","wikidata":"https://www.wikidata.org/wiki/Q1524945","display_name":"Ternary operation","level":2,"score":0.43783196806907654},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38061708211898804},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3432180881500244},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.33222496509552},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.29298511147499084},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ismvl52857.2022.00035","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismvl52857.2022.00035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 52nd International Symposium on Multiple-Valued Logic (ISMVL)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321034","display_name":"New Energy and Industrial Technology Development Organization","ror":"https://ror.org/0055k7a87"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2750384547","https://openalex.org/W2970691381","https://openalex.org/W3093982621","https://openalex.org/W3118841097","https://openalex.org/W3161115651","https://openalex.org/W3176182871"],"related_works":["https://openalex.org/W2798215405","https://openalex.org/W2990962948","https://openalex.org/W2084169748","https://openalex.org/W2127529229","https://openalex.org/W2355515259","https://openalex.org/W3204400881","https://openalex.org/W3214410901","https://openalex.org/W3204296682","https://openalex.org/W3183118997","https://openalex.org/W2917767146"],"abstract_inverted_index":{"The":[0,142,242],"use":[1],"of":[2,20,91,133,145,219,229,244],"machine":[3,40],"learning":[4,41],"is":[5,36,49,62,97,247],"expanding":[6],"in":[7,14,29,59,73,122,139,159],"various":[8,173,183,204],"applications":[9],"such":[10],"as":[11],"image":[12],"processing":[13,34,70],"data":[15,60,177],"centers.":[16],"With":[17],"the":[18,33,54,86,123,131,140,146,163,195,209,220,227,245,255],"spread":[19],"deep":[21],"learning,":[22],"neural-network-based":[23],"models":[24],"have":[25],"frequently":[26],"been":[27],"adopted":[28],"recent":[30],"years.":[31],"Because":[32],"speed":[35],"slow":[37],"when":[38],"evaluating":[39],"on":[42,254],"a":[43,45,74,81,92,114,120,213],"CPU,":[44],"fast-dedicated":[46],"hardware":[47,57],"accelerator":[48],"often":[50],"used.":[51],"In":[52],"particular,":[53],"demand":[55],"for":[56,80,108,178,189,198,236],"accelerators":[58],"centers":[61],"increasing.":[63],"A":[64],"low":[65],"power":[66],"consumption":[67],"and":[68,153,182],"high-speed":[69],"are":[71,103,172],"required":[72,231],"limited":[75],"space.":[76],"An":[77,201],"implementation":[78],"method":[79,197],"ternary":[82,168,239],"neural":[83,100,169,191,240],"network":[84],"utilizing":[85],"rewritable":[87],"look-up":[88],"table":[89],"(LUT)":[90],"field-programmable":[93],"gate":[94],"array":[95],"(FPGA)":[96],"proposed.":[98],"Binary/ternary":[99],"networks,":[101],"which":[102,250],"quantized":[104],"to":[105,110,136,156,175,185,217,232],"1\u20132":[106],"bits":[107,135],"mapping":[109],"LUTs,":[111],"suffer":[112],"from":[113],"poor":[115],"recognition":[116,124,214],"accuracy.":[117],"To":[118],"prevent":[119],"decrease":[121],"accuracy,":[125],"let":[126],"<tex":[127,149],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[128,150],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$q$</tex>":[129],"be":[130,137,157,252],"number":[132],"quantization":[134],"stored":[138],"LUT.":[141],"memory":[143,230],"size":[144,243],"LUT":[147,235,246],"becomes":[148],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$O(2^{q})$</tex>":[151],"bits,":[152],"it":[154],"tends":[155],"exponential":[158],"size.":[160],"We":[161,193,224],"improved":[162],"accuracy":[164,215],"using":[165,203],"an":[166,234,237],"ensemble":[167,210,238],"network.":[170,241],"There":[171],"ways":[174,184],"select":[176,186],"ensembles":[179],"during":[180],"training,":[181],"branch":[187],"pruning":[188],"trivialized":[190],"networks.":[192],"chose":[194],"greedy":[196],"our":[199],"design.":[200],"evaluation":[202],"benchmark":[205],"datasets":[206],"showed":[207],"that":[208,218],"approach":[211],"achieved":[212],"equivalent":[216],"32-bit":[221],"float":[222],"model.":[223],"also":[225],"estimated":[226],"amount":[228],"implement":[233],"1.9":[248],"Mbit,":[249],"can":[251],"realized":[253],"current":[256],"FPGAs.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}