{"id":"https://openalex.org/W7147008391","doi":"https://doi.org/10.1109/cnml68938.2026.11452485","title":"Acceleration of YOLOv5 Object Detection Model Based on FPGA","display_name":"Acceleration of YOLOv5 Object Detection Model Based on FPGA","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147008391","doi":"https://doi.org/10.1109/cnml68938.2026.11452485"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11452485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","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/A5075689961","display_name":"Yuan Zhao","orcid":"https://orcid.org/0000-0003-3799-489X"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaodong Zhao","raw_affiliation_strings":["Hunan University,School of Physics and Electronics,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,School of Physics and Electronics,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132691972","display_name":"Shuting Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shuting Wang","raw_affiliation_strings":["Hong Kong Baptist University,School of Business,China"],"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University,School of Business,China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072042283","display_name":"Zhendao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendao Wang","raw_affiliation_strings":["Hunan University,School of Physics and Electronics,Changsha,China"],"affiliations":[{"raw_affiliation_string":"Hunan University,School of Physics and Electronics,Changsha,China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075689961"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84872865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"987","last_page":"990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4731000065803528,"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":0.4731000065803528,"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/T14347","display_name":"Big Data and Digital Economy","score":0.06889999657869339,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.04699999839067459,"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/bottleneck","display_name":"Bottleneck","score":0.7401999831199646},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6082000136375427},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5806999802589417},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.579200029373169},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5773000121116638},{"id":"https://openalex.org/keywords/frame-rate","display_name":"Frame rate","score":0.5311999917030334},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5013999938964844},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4431000053882599},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.42989999055862427}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7401999831199646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699999988079071},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6082000136375427},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5806999802589417},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.579200029373169},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5773000121116638},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.5311999917030334},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5055000185966492},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5013999938964844},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.43720000982284546},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C2779030575","wikidata":"https://www.wikidata.org/wiki/Q827773","display_name":"Verilog","level":3,"score":0.42910000681877136},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.42640000581741333},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.42500001192092896},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42080000042915344},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4196000099182129},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.32179999351501465},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.303600013256073},{"id":"https://openalex.org/C118993495","wikidata":"https://www.wikidata.org/wiki/Q5042828","display_name":"Electrical efficiency","level":3,"score":0.30070000886917114},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.2948000133037567},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.25189998745918274},{"id":"https://openalex.org/C2778571676","wikidata":"https://www.wikidata.org/wiki/Q3317826","display_name":"ModelSim","level":4,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11452485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2094756095","https://openalex.org/W2935524202","https://openalex.org/W3013082411","https://openalex.org/W3035946844","https://openalex.org/W3206315185","https://openalex.org/W4391687066","https://openalex.org/W4394568454","https://openalex.org/W4402082638","https://openalex.org/W4402632708","https://openalex.org/W4402643761","https://openalex.org/W4415222974"],"related_works":[],"abstract_inverted_index":{"To":[0],"meet":[1],"the":[2,27,52,67,76,107,116,120,125,143],"demand":[3],"for":[4,142],"efficient":[5,138],"deployment":[6],"of":[7,69,83,91,103,118,123,146],"object":[8,148],"detection":[9,149],"in":[10],"edge":[11,151],"scenarios,":[12],"this":[13],"paper":[14],"proposes":[15],"a":[16,81,100,128],"hardware":[17,144],"acceleration":[18,77],"scheme":[19,141],"based":[20],"on":[21,26,150],"YOLOv5n":[22],"and":[23,51,133,139],"implements":[24],"it":[25],"ZYNQ7100":[28],"platform.":[29],"The":[30,40],"circuit":[31],"design":[32,126],"is":[33,44,56,110],"carried":[34],"out":[35],"using":[36],"pure":[37],"Verilog":[38],"language.":[39],"ping-pong":[41],"double-buffer":[42],"mechanism":[43],"adopted":[45],"to":[46,58,99],"optimize":[47],"data":[48,70],"transmission":[49],"efficiency,":[50],"inter-layer":[53],"pipeline":[54],"architecture":[55],"integrated":[57],"enhance":[59],"parallel":[60],"processing":[61],"capability,":[62],"which":[63],"effectively":[64],"breaks":[65],"through":[66],"bottleneck":[68],"throughput.":[71],"Experimental":[72],"results":[73],"show":[74],"that":[75],"system":[78],"operates":[79],"at":[80,112],"frequency":[82],"200":[84],"MHz,":[85],"with":[86],"an":[87,137],"average":[88],"inference":[89],"time":[90],"only":[92],"17.29":[93],"ms":[94],"per":[95],"frame":[96,101],"image,":[97],"corresponding":[98],"rate":[102],"57.8":[104],"fps,":[105],"while":[106],"power":[108],"consumption":[109],"controlled":[111],"7.52":[113],"W.":[114],"On":[115],"premise":[117],"ensuring":[119],"real-time":[121],"performance":[122,132],"detection,":[124],"achieves":[127],"good":[129],"balance":[130],"between":[131],"resource":[134],"utilization,":[135],"providing":[136],"feasible":[140],"implementation":[145],"lightweight":[147],"devices.":[152]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-04-02T00:00:00"}
