{"id":"https://openalex.org/W4408862768","doi":"https://doi.org/10.1109/icce63647.2025.10930191","title":"A Winograd-Convolution-Based Accelerator on FPGA for Real-Time Object Detection with Effective On-Chip Buffer Access Patterns","display_name":"A Winograd-Convolution-Based Accelerator on FPGA for Real-Time Object Detection with Effective On-Chip Buffer Access Patterns","publication_year":2025,"publication_date":"2025-01-11","ids":{"openalex":"https://openalex.org/W4408862768","doi":"https://doi.org/10.1109/icce63647.2025.10930191"},"language":"en","primary_location":{"id":"doi:10.1109/icce63647.2025.10930191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","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/A5113296003","display_name":"Keehyuk Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keehyuk Lee","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072544388","display_name":"Mincheol Cha","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mincheol Cha","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088587799","display_name":"Soosung Kim","orcid":"https://orcid.org/0009-0002-4430-7752"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soosung Kim","raw_affiliation_strings":["School of Electical and Electronics Engineering, Chung-Ang University,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electical and Electronics Engineering, Chung-Ang University,South Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014900695","display_name":"Xuan Truong Nguyen","orcid":"https://orcid.org/0000-0002-7527-6971"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Xuan Truong Nguyen","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024723558","display_name":"Hyuk\u2010Jae Lee","orcid":"https://orcid.org/0000-0001-6811-9647"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuk-Jae Lee","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0704,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.76329104,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9955999851226807,"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":0.9955999851226807,"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/T10904","display_name":"Embedded Systems Design Techniques","score":0.9592000246047974,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9487000107765198,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8054518699645996},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.727800190448761},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6962746381759644},{"id":"https://openalex.org/keywords/buffer","display_name":"Buffer (optical fiber)","score":0.6168704628944397},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5684141516685486},{"id":"https://openalex.org/keywords/chip","display_name":"Chip","score":0.5282541513442993},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.4564511775970459},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.453429639339447},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4246803820133209},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.39651355147361755},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.38970234990119934},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21225613355636597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.10842594504356384},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07015994191169739}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8054518699645996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727800190448761},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6962746381759644},{"id":"https://openalex.org/C145018004","wikidata":"https://www.wikidata.org/wiki/Q4985944","display_name":"Buffer (optical fiber)","level":2,"score":0.6168704628944397},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5684141516685486},{"id":"https://openalex.org/C165005293","wikidata":"https://www.wikidata.org/wiki/Q1074500","display_name":"Chip","level":2,"score":0.5282541513442993},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.4564511775970459},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.453429639339447},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4246803820133209},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.39651355147361755},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.38970234990119934},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21225613355636597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.10842594504356384},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07015994191169739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce63647.2025.10930191","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930191","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5333152913","display_name":null,"funder_award_id":"IITP-2023-RS-2023-00256081","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W2094756095","https://openalex.org/W2172654076","https://openalex.org/W2276486856","https://openalex.org/W2523838129","https://openalex.org/W2765235648","https://openalex.org/W2766839578","https://openalex.org/W2783538964","https://openalex.org/W2785545076","https://openalex.org/W2886623847","https://openalex.org/W2963037989","https://openalex.org/W2997106510","https://openalex.org/W3018105153","https://openalex.org/W3091140859","https://openalex.org/W3200985460","https://openalex.org/W3206315185","https://openalex.org/W4214745146","https://openalex.org/W4214870144","https://openalex.org/W4223637989","https://openalex.org/W4249932213","https://openalex.org/W4323831235","https://openalex.org/W6775260854","https://openalex.org/W6859335934"],"related_works":["https://openalex.org/W2097227107","https://openalex.org/W2366025885","https://openalex.org/W4233342643","https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2007889530","https://openalex.org/W2518118925","https://openalex.org/W3159273459"],"abstract_inverted_index":{"A":[0],"convolutional":[1],"neural":[2],"network":[3],"(CNN)":[4],"based":[5],"object":[6,38,84],"detector":[7],"typically":[8],"requires":[9,53],"billions":[10],"of":[11,28,110,125,183,195,202],"multiplications,":[12,29],"making":[13],"it":[14,52],"difficult":[15],"to":[16,100,115,185],"achieve":[17],"a":[18,42,77,95,108,130,136,150,167,181,187,193,206],"real-time":[19,44,83,207],"end-to-end":[20],"inference":[21,186],"on":[22,47,80,153,166,205],"FPGA.":[23],"To":[24,70,121],"reduce":[25],"the":[26,72,126,154,199],"number":[27],"Winograd":[30],"convolution":[31],"(WinoConv)":[32],"appears":[33],"promising":[34],"in":[35,144,192],"accelerating":[36],"CNN-based":[37],"detectors.":[39],"However,":[40],"designing":[41],"generic":[43],"WinoConv-based":[45,78],"accelerator":[46],"FPGA":[48,81,171],"is":[49,159],"challenging":[50],"since":[51],"effectively":[54],"executing":[55],"various":[56],"layers,":[57],"for":[58,82,149],"example,":[59],"3\u00d73":[60],"and":[61,68,104,164,215],"1":[62,67],"\u00d71":[63],"layers":[64],"with":[65,86,107,161],"strides":[66],"2.":[69],"address":[71],"problem,":[73],"this":[74],"paper":[75],"proposes":[76],"engine":[79,158,179,211],"detection":[85],"effective":[87,98],"line":[88],"buffer":[89],"access":[90],"patterns.":[91],"Specifically,":[92],"we":[93,128],"propose":[94],"simple":[96],"yet":[97],"dataflow":[99],"process":[101],"tiled":[102],"input":[103],"output":[105],"tensors":[106],"stride":[109],"2,":[111],"mitigating":[112],"an":[113],"overhead":[114],"reorder":[116],"feature":[117],"maps":[118],"between":[119],"layers.":[120],"enable":[122],"practical":[123],"use":[124],"engine,":[127],"introduce":[129],"hardware-friendly":[131],"post-training":[132],"quantization":[133],"scheme,":[134],"achieving":[135],"negligible":[137],"accuracy":[138],"drop,":[139],"i.e.,":[140],"less":[141],"than":[142],"1%":[143],"mean":[145],"average":[146],"precision":[147],"(mAP)":[148],"Tiny-YOLOv3":[151,189],"model":[152],"VOC":[155],"dataset.":[156],"Our":[157],"implemented":[160],"Verilog":[162],"HDL":[163],"deployed":[165],"Xilinx":[168],"Zynq":[169],"ZCU106":[170],"board.":[172],"The":[173,210],"experimental":[174],"results":[175],"show":[176],"that":[177],"our":[178],"achieves":[180],"latency":[182],"5.134ms":[184],"custom":[188],"model,":[190],"resulting":[191],"throughput":[194],"292.18":[196],"GOPS":[197],"at":[198],"clock":[200],"frequency":[201],"125":[203],"MHz":[204],"video":[208],"stream.":[209],"utilizes":[212],"1053":[213],"DSPs":[214],"105":[216],"BRAM.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}