{"id":"https://openalex.org/W3091140859","doi":"https://doi.org/10.1109/iscas45731.2020.9180843","title":"Accelerating Tiny YOLOv3 using FPGA-Based Hardware/Software Co-Design","display_name":"Accelerating Tiny YOLOv3 using FPGA-Based Hardware/Software Co-Design","publication_year":2020,"publication_date":"2020-09-29","ids":{"openalex":"https://openalex.org/W3091140859","doi":"https://doi.org/10.1109/iscas45731.2020.9180843","mag":"3091140859"},"language":"en","primary_location":{"id":"doi:10.1109/iscas45731.2020.9180843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5060826708","display_name":"Afzal Ahmad","orcid":"https://orcid.org/0000-0003-4491-5440"},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Afzal Ahmad","raw_affiliation_strings":["Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan","institution_ids":["https://openalex.org/I207789805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069432255","display_name":"Muhammad Adeel Pasha","orcid":"https://orcid.org/0000-0001-9892-5201"},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Adeel Pasha","raw_affiliation_strings":["Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan","institution_ids":["https://openalex.org/I207789805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059124356","display_name":"Ghulam Jilani Raza","orcid":null},"institutions":[{"id":"https://openalex.org/I207789805","display_name":"Lahore University of Management Sciences","ror":"https://ror.org/05b5x4a35","country_code":"PK","type":"education","lineage":["https://openalex.org/I207789805"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Ghulam Jilani Raza","raw_affiliation_strings":["Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan","institution_ids":["https://openalex.org/I207789805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I207789805"],"apc_list":null,"apc_paid":null,"fwci":2.3494,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.90615744,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"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/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9993000030517578,"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9984999895095825,"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8237209320068359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8202685117721558},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6944611072540283},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6873847246170044},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5688628554344177},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.5407848358154297},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5403149127960205},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5028941035270691},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4825798571109772},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4309088885784149},{"id":"https://openalex.org/keywords/reconfigurable-computing","display_name":"Reconfigurable computing","score":0.41660448908805847},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4155752658843994},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.39351385831832886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3260849118232727}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8237209320068359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8202685117721558},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6944611072540283},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6873847246170044},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5688628554344177},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.5407848358154297},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5403149127960205},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5028941035270691},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4825798571109772},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4309088885784149},{"id":"https://openalex.org/C142962650","wikidata":"https://www.wikidata.org/wiki/Q240838","display_name":"Reconfigurable computing","level":3,"score":0.41660448908805847},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4155752658843994},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.39351385831832886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3260849118232727},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas45731.2020.9180843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas45731.2020.9180843","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2193145675","https://openalex.org/W2294282016","https://openalex.org/W2552194367","https://openalex.org/W2612445135","https://openalex.org/W2786624244","https://openalex.org/W2796347433","https://openalex.org/W2892129534","https://openalex.org/W2900316824","https://openalex.org/W2918845477","https://openalex.org/W2963125010","https://openalex.org/W2963351448","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W4297775537","https://openalex.org/W6730270785","https://openalex.org/W6737664043","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2995926156","https://openalex.org/W2063534976","https://openalex.org/W2284838239","https://openalex.org/W2591834580","https://openalex.org/W4239107643","https://openalex.org/W2113648965","https://openalex.org/W2473740624","https://openalex.org/W2150194641","https://openalex.org/W2147614424","https://openalex.org/W4295855328"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"are":[4,42,64],"influencing":[5],"major":[6],"breakthroughs":[7],"in":[8,119,128],"computer":[9],"vision":[10,84],"by":[11,107],"achieving":[12],"unprecedented":[13],"accuracy":[14],"on":[15],"tasks":[16],"such":[17],"as":[18,69],"image":[19],"classification,":[20],"object":[21,104,140],"detection,":[22],"landmark":[23],"detection":[24,105,141],"and":[25],"semantic":[26],"segmentation.":[27],"Owing":[28],"to":[29,45,94,133],"high":[30,52],"computational":[31],"complexity":[32],"of":[33,131,138],"most":[34,115],"modern":[35],"CNN":[36,101],"architectures,":[37],"graphical":[38],"processing":[39],"units":[40],"(GPUs)":[41],"being":[43],"utilized":[44],"achieve":[46],"real-time":[47],"performance":[48,73,126],"albeit":[49],"at":[50],"a":[51,109],"energy":[53,77],"cost.":[54],"Consequently,":[55],"Field":[56],"Programmable":[57],"Gate":[58],"Arrays":[59],"(FPGAs)":[60],"based":[61],"hardware":[62,110],"accelerators":[63],"also":[65],"making":[66],"their":[67],"way":[68],"they":[70],"demonstrate":[71],"GPU-like":[72],"with":[74],"significantly":[75],"lower":[76],"consumption":[78],"that":[79],"is":[80],"well-suited":[81],"for":[82,103,112],"embedded":[83],"applications.":[85],"In":[86],"this":[87],"paper,":[88],"we":[89],"employ":[90],"Hardware/Software":[91],"Co-Design":[92],"approach":[93],"accelerate":[95],"Tiny":[96],"YOLOv3":[97],"-":[98,106],"an":[99],"efficient":[100,139],"architecture":[102],"designing":[108],"accelerator":[111],"convolution,":[113],"the":[114,120,129],"complex":[116],"operation":[117],"involved":[118],"CNNs.":[121],"Experimental":[122],"results":[123],"show":[124],"significant":[125],"gains,":[127],"range":[130],"3.9\u00d7":[132],"21.3\u00d7,":[134],"over":[135],"previous":[136],"implementations":[137],"algorithms.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
