{"id":"https://openalex.org/W4207029376","doi":"https://doi.org/10.1109/ssci50451.2021.9659887","title":"Adaptive Integer Quantisation for Convolutional Neural Networks through Evolutionary Algorithms","display_name":"Adaptive Integer Quantisation for Convolutional Neural Networks through Evolutionary Algorithms","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4207029376","doi":"https://doi.org/10.1109/ssci50451.2021.9659887"},"language":"en","primary_location":{"id":"doi:10.1109/ssci50451.2021.9659887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659887","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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/A5100389366","display_name":"Ziwei Wang","orcid":"https://orcid.org/0000-0001-9225-8495"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ziwei Wang","raw_affiliation_strings":["University of York, York, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of York, York, United Kingdom","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056241158","display_name":"Martin A. Trefzer","orcid":"https://orcid.org/0000-0002-6196-6832"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Martin A. Trefzer","raw_affiliation_strings":["University of York, York, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of York, York, United Kingdom","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034601593","display_name":"Simon J. Bale","orcid":"https://orcid.org/0000-0002-3361-5648"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon J. Bale","raw_affiliation_strings":["University of York, York, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of York, York, United Kingdom","institution_ids":["https://openalex.org/I52099693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048789717","display_name":"Andy M. Tyrrell","orcid":"https://orcid.org/0000-0002-8533-2404"},"institutions":[{"id":"https://openalex.org/I52099693","display_name":"University of York","ror":"https://ror.org/04m01e293","country_code":"GB","type":"education","lineage":["https://openalex.org/I52099693"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andy M. Tyrrell","raw_affiliation_strings":["University of York, York, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of York, York, United Kingdom","institution_ids":["https://openalex.org/I52099693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100389366"],"corresponding_institution_ids":["https://openalex.org/I52099693"],"apc_list":null,"apc_paid":null,"fwci":0.1307,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.51627304,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9937999844551086,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9927999973297119,"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":0.6953532099723816},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6465297341346741},{"id":"https://openalex.org/keywords/integer","display_name":"Integer (computer science)","score":0.5656659603118896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5441895127296448},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.497698575258255},{"id":"https://openalex.org/keywords/floating-point","display_name":"Floating point","score":0.45476844906806946},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.44015738368034363},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.42604756355285645},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41690096259117126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26758888363838196},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.07865813374519348}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953532099723816},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6465297341346741},{"id":"https://openalex.org/C97137487","wikidata":"https://www.wikidata.org/wiki/Q729138","display_name":"Integer (computer science)","level":2,"score":0.5656659603118896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5441895127296448},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.497698575258255},{"id":"https://openalex.org/C84211073","wikidata":"https://www.wikidata.org/wiki/Q117879","display_name":"Floating point","level":2,"score":0.45476844906806946},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.44015738368034363},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.42604756355285645},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41690096259117126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26758888363838196},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.07865813374519348},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssci50451.2021.9659887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssci50451.2021.9659887","pdf_url":null,"source":{"id":"https://openalex.org/S4363604921","display_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","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":43,"referenced_works":["https://openalex.org/W658797333","https://openalex.org/W1522301498","https://openalex.org/W1634005169","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1724438581","https://openalex.org/W1841592590","https://openalex.org/W1999713473","https://openalex.org/W2045491133","https://openalex.org/W2097117768","https://openalex.org/W2107626243","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2127088021","https://openalex.org/W2163605009","https://openalex.org/W2233116163","https://openalex.org/W2286365479","https://openalex.org/W2300242332","https://openalex.org/W2319920447","https://openalex.org/W2469490737","https://openalex.org/W2565125333","https://openalex.org/W2765235648","https://openalex.org/W2786216825","https://openalex.org/W2809624076","https://openalex.org/W2818275232","https://openalex.org/W2952899695","https://openalex.org/W2957513053","https://openalex.org/W3012480085","https://openalex.org/W3118608800","https://openalex.org/W4255158661","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6637709462","https://openalex.org/W6638783484","https://openalex.org/W6683826617","https://openalex.org/W6684191040","https://openalex.org/W6696004547","https://openalex.org/W6700264148","https://openalex.org/W6720242923","https://openalex.org/W6736497209","https://openalex.org/W6753069482","https://openalex.org/W6775076665"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2074043759","https://openalex.org/W4293226380","https://openalex.org/W4225949190","https://openalex.org/W3028347934","https://openalex.org/W3009327594","https://openalex.org/W2185692674","https://openalex.org/W2803935332"],"abstract_inverted_index":{"State-of-the-art":[0],"Convolutional":[1],"Neural":[2],"Networks":[3],"(CNNs)":[4],"have":[5,58],"become":[6],"increasingly":[7],"accurate.":[8],"However,":[9],"hundreds":[10],"or":[11],"thousands":[12],"of":[13,105,133,176],"megabytes":[14],"data":[15],"are":[16,37],"involved":[17],"to":[18,38,59,78,91,125,142,159,179],"store":[19],"them,":[20],"making":[21],"these":[22],"networks":[23],"also":[24],"computationally":[25],"expensive.":[26],"For":[27],"certain":[28],"applications,":[29],"such":[30,35],"as":[31],"Internet-of-Things":[32],"(IoT),":[33],"where":[34],"CNNs":[36,178],"be":[39,60],"implemented":[40],"on":[41,111],"resource-constrained":[42],"and":[43,51,56,62,136],"memory-constrained":[44],"platforms,":[45],"including":[46],"Field-Programmable":[47],"Gate":[48],"Arrays":[49],"(FPGAs)":[50],"embedded":[52],"devices,":[53],"CNN":[54],"architectures":[55],"parameters":[57],"small":[61,113],"efficient.":[63],"In":[64],"this":[65],"paper,":[66],"an":[67],"evolutionary":[68,89],"algorithm":[69],"(EA)":[70],"based":[71],"adaptive":[72,131,164],"integer":[73,144],"quantisation":[74,95,132,156,165],"method":[75,84,108,173],"is":[76,109,124,174],"proposed":[77,83,107,163,172],"reduce":[79],"network":[80],"size.":[81],"The":[82,103,122,151,167],"uses":[85],"single":[86],"objective":[87],"rank-based":[88],"strategy":[90],"find":[92],"the":[93,106,115,119,162,171],"best":[94],"bin":[96],"boundary":[97],"for":[98,146],"fixed":[99],"quantised":[100],"bit":[101,181],"width.":[102],"performance":[104],"evaluated":[110],"a":[112,127,186],"CNN,":[114],"LeNet-5":[116],"architecture,":[117],"using":[118],"CIFAR-10":[120],"dataset.":[121],"aim":[123],"devise":[126],"methodology":[128],"that":[129,170],"allows":[130],"both":[134],"weights":[135],"bias":[137],"from":[138,157],"32-bit":[139],"floating":[140],"point":[141],"8-bit":[143],"representation":[145,183],"LeNet-5,":[147],"while":[148],"retaining":[149],"accuracy.":[150,191],"experiments":[152],"compare":[153],"straight-forward":[154],"(linear)":[155],"32-bits":[158],"8-bits":[160],"with":[161,184],"method.":[166],"results":[168],"show":[169],"capable":[175],"quantising":[177],"lower":[180],"width":[182],"only":[185],"slight":[187],"loss":[188],"in":[189],"classification":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}