{"id":"https://openalex.org/W4384787602","doi":"https://doi.org/10.1109/access.2023.3296429","title":"Integrated Imager and 3.22 <i>\u03bc</i>s/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing","display_name":"Integrated Imager and 3.22 <i>\u03bc</i>s/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4384787602","doi":"https://doi.org/10.1109/access.2023.3296429"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3296429","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3296429","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185926.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185926.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069205756","display_name":"Ruizhi Wang","orcid":"https://orcid.org/0000-0001-9732-6768"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ruizhi Wang","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9732-6768","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103793847","display_name":"Cheng-Hsuan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Cheng-Hsuan Wu","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003282110","display_name":"Makoto Takamiya","orcid":"https://orcid.org/0000-0003-0289-7790"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Takamiya","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-0289-7790","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.1161,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40105415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"74364","last_page":"74378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.998199999332428,"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/T14158","display_name":"Optical Systems and Laser Technology","score":0.9966999888420105,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138909101486206},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6632982492446899},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6201762557029724},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4508783221244812},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4412403404712677},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.44057080149650574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39236003160476685},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18330776691436768},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.10329043865203857},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09012243151664734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138909101486206},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6632982492446899},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6201762557029724},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4508783221244812},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4412403404712677},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.44057080149650574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39236003160476685},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18330776691436768},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.10329043865203857},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09012243151664734},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3296429","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3296429","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185926.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d5103e7221c14c71996bdb3516541686","is_oa":true,"landing_page_url":"https://doaj.org/article/d5103e7221c14c71996bdb3516541686","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 74364-74378 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3296429","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3296429","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10185926.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6810934274","display_name":"Integration of Image Sensor and Analog CNN Circuits Reducing Image Recognition Energy by Factor of 1/1000","funder_award_id":"19H02188","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384787602.pdf","grobid_xml":"https://content.openalex.org/works/W4384787602.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1005811612","https://openalex.org/W2289252105","https://openalex.org/W2584616277","https://openalex.org/W2591601611","https://openalex.org/W2592539811","https://openalex.org/W2593197747","https://openalex.org/W2593564159","https://openalex.org/W2766143712","https://openalex.org/W2894696827","https://openalex.org/W2907482724","https://openalex.org/W2945146780","https://openalex.org/W2955586082","https://openalex.org/W2972169167","https://openalex.org/W2972984303","https://openalex.org/W2979359179","https://openalex.org/W2981240739","https://openalex.org/W3011368285","https://openalex.org/W3034870003","https://openalex.org/W3092475999","https://openalex.org/W3094075356","https://openalex.org/W3096649732","https://openalex.org/W3101033942","https://openalex.org/W3104775050","https://openalex.org/W3120016950","https://openalex.org/W3133578396","https://openalex.org/W3133725905","https://openalex.org/W3174208823","https://openalex.org/W3201629247","https://openalex.org/W4220936377","https://openalex.org/W4221017297","https://openalex.org/W4308485573","https://openalex.org/W4312050964","https://openalex.org/W6734759595","https://openalex.org/W6762542060","https://openalex.org/W6791142990"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W4399188509"],"abstract_inverted_index":{"This":[0,75,142,187,214,227],"paper":[1],"presents":[2],"an":[3],"innovative":[4],"approach":[5,77],"to":[6,42,47,88,156,222],"achieve":[7],"ultralow-latency":[8],"convolutional":[9,70],"neural":[10,71],"network":[11,72],"(CNN)":[12],"processing,":[13,137],"which":[14,83],"is":[15],"critical":[16],"for":[17,55,236],"real-time":[18,44],"image":[19,56,140,255],"processing":[20,54,81,107,159,230,237],"applications":[21],"such":[22],"as":[23],"autonomous":[24],"driving":[25],"and":[26,37,108,120,169,177,207,242],"virtual":[27],"reality.":[28],"Traditional":[29],"CNN":[30],"accelerators":[31],"employing":[32],"in/near-array-computing":[33],"(inclusive":[34],"of":[35,135,139,148,151,192,204,211,219],"in/near-memory-computing":[36],"in/near-sensor-computing)":[38],"architectures":[39],"have":[40,167],"struggled":[41],"meet":[43],"requirements":[45],"due":[46],"latency":[48,103,191,217],"bottlenecks":[49],"encountered":[50],"with":[51,105,244],"conventional":[52,157],"column-parallel":[53,158],"processing.":[57,256],"To":[58],"address":[59],"this":[60,117],"challenge,":[61],"we":[62],"propose":[63],"a":[64,79,97,124,145,171,182,190,201,208,216,250],"novel,":[65],"all-digital":[66],"in-imager":[67],"global-parallel":[68,80,136,229],"binary":[69],"(IIGP-BNN)":[73],"accelerator.":[74],"new":[76],"employs":[78],"concept,":[82],"enables":[84],"multiply-and-accumulate":[85],"operations":[86,122],"(MACs)":[87],"be":[89],"executed":[90],"simultaneously":[91],"within":[92,131],"the":[93,101,196,223,234,245],"imager":[94,176],"array":[95],"in":[96,144,240,253],"2D":[98],"manner,":[99],"eliminating":[100],"additional":[102],"associated":[104],"row-by-row":[106],"data":[109],"access":[110,113],"from":[111],"random":[112],"memories":[114],"(RAMs).":[115],"In":[116],"design,":[118],"convolution":[119,199],"subsampling":[121],"using":[123,181],"3":[125,127],"\u00d7":[126,173],"kernel":[128],"are":[129],"completed":[130],"just":[132],"nine":[133],"steps":[134],"regardless":[138],"size.":[141],"results":[143],"theoretical":[146],"reduction":[147,218],"over":[149],"88.5%":[150],"repeated":[152],"row":[153],"scans":[154],"compared":[155,221],"architectures,":[160],"thus":[161],"significantly":[162],"reducing":[163],"computing":[164],"latency.":[165],"We":[166],"designed":[168],"prototyped":[170],"30":[172,174],"integrated":[175],"IIGP-BNN":[178],"accelerator":[179],"IC":[180],"0.18":[183],"\u03bcm":[184],"CMOS":[185],"process.":[186],"prototype":[188],"achieved":[189],"3.22":[193],"\u03bcs/kernel":[194],"on":[195],"first":[197],"layer":[198],"at":[200],"power":[202],"supply":[203],"1":[205],"V":[206],"clock":[209],"frequency":[210],"35.7":[212],"MHz.":[213],"represents":[215],"35.6%":[220],"state-of-the-art":[224],"in/near-imager-computing":[225],"works.":[226],"proposed":[228],"concept":[231],"opens":[232],"up":[233],"potential":[235],"high-resolution":[238],"images":[239],"4K":[241],"8K":[243],"same":[246],"ultralow":[247],"latency,":[248],"marking":[249],"significant":[251],"advancement":[252],"high-speed":[254]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-07-20T00:00:00"}