{"id":"https://openalex.org/W3108553883","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258103","title":"An Efficient Accelerator for Deep Convolutional Neural Networks","display_name":"An Efficient Accelerator for Deep Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3108553883","doi":"https://doi.org/10.1109/icce-taiwan49838.2020.9258103","mag":"3108553883"},"language":"en","primary_location":{"id":"doi:10.1109/icce-taiwan49838.2020.9258103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","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/A5075959586","display_name":"Yi-Xian Kuo","orcid":null},"institutions":[{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yi-Xian Kuo","raw_affiliation_strings":["Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan","institution_ids":["https://openalex.org/I162838928"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008507157","display_name":"Yeong-Kang Lai","orcid":"https://orcid.org/0000-0002-5465-7935"},"institutions":[{"id":"https://openalex.org/I162838928","display_name":"National Chung Hsing University","ror":"https://ror.org/05vn3ca78","country_code":"TW","type":"education","lineage":["https://openalex.org/I162838928"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yeong-Kang Lai","raw_affiliation_strings":["Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan","institution_ids":["https://openalex.org/I162838928"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075959586"],"corresponding_institution_ids":["https://openalex.org/I162838928"],"apc_list":null,"apc_paid":null,"fwci":0.0977,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.420935,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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":0.9975000023841858,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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":0.9886999726295471,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7657968997955322},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7396417856216431},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44231560826301575}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7657968997955322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7396417856216431},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44231560826301575}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-taiwan49838.2020.9258103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-taiwan49838.2020.9258103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2945146780","https://openalex.org/W2963037989","https://openalex.org/W2963122961"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4293226380","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,41],"networks":[2,42],"(CNN)":[3],"in":[4,10,36,119,145,173],"deep":[5],"learning":[6],"have":[7],"become":[8],"popular":[9],"many":[11],"of":[12,46,95,122,137,162],"the":[13,52,63,93,120,131,135,138,141,156,159],"latest":[14],"applications":[15],"from":[16],"speech":[17],"recognition":[18],"to":[19,57,60,67,78,91,116,133,154],"image":[20],"classification":[21],"and":[22,48,98,104,125],"object":[23,37],"detection.":[24,38],"Among":[25],"them,":[26],"YOLO":[27,39],"(You":[28],"only":[29,113],"look":[30],"once)":[31],"is":[32,80,84,90,152,165],"a":[33,44,71],"well-known":[34],"algorithm":[35],"convolutional":[40],"require":[43],"lot":[45],"multiplication":[47,118],"accumulation":[49],"calculations.":[50],"On":[51],"edge,":[53],"special":[54],"hardware":[55,69],"needs":[56],"be":[58],"designed":[59],"speed":[61,103],"up":[62],"calculation.":[64],"In":[65,143],"order":[66],"reduce":[68,92,155],"costs,":[70],"new":[72],"distributed":[73],"arithmetic":[74],"(DA)":[75],"architecture":[76],"similar":[77],"NEDA":[79],"proposed.":[81],"The":[82,88],"multipliers":[83],"replaced":[85],"by":[86],"adders.":[87],"purpose":[89],"cost":[94],"power":[96],"consumption":[97],"area":[99],"while":[100],"maintaining":[101],"high":[102,105],"precision.":[106],"Mathematical":[107],"analysis":[108],"proves":[109],"that":[110,166],"DA":[111],"can":[112,168],"use":[114],"addition":[115],"achieve":[117],"form":[121],"two's":[123],"complement,":[124],"then":[126],"perform":[127,169],"data":[128],"shift":[129],"at":[130],"end":[132],"implement":[134],"operation":[136],"adder,":[139],"not":[140],"multiplier.":[142],"addition,":[144],"this":[146,163],"paper,":[147],"after":[148],"convolution,":[149],"maximum":[150],"pooling":[151],"performed":[153],"bandwidth.":[157],"Finally,":[158],"biggest":[160],"feature":[161],"article":[164],"PE":[167],"1.78":[170],"MAC":[171],"operations":[172],"one":[174],"clock":[175],"cycle.":[176]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}