{"id":"https://openalex.org/W4220783100","doi":"https://doi.org/10.1109/icce53296.2022.9730159","title":"Object Detection Edge Performance Optimization on FPGA-Based Heterogeneous Multiprocessor Systems","display_name":"Object Detection Edge Performance Optimization on FPGA-Based Heterogeneous Multiprocessor Systems","publication_year":2022,"publication_date":"2022-01-07","ids":{"openalex":"https://openalex.org/W4220783100","doi":"https://doi.org/10.1109/icce53296.2022.9730159"},"language":"en","primary_location":{"id":"doi:10.1109/icce53296.2022.9730159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce53296.2022.9730159","pdf_url":null,"source":{"id":"https://openalex.org/S4363608007","display_name":"2022 IEEE International Conference on Consumer Electronics (ICCE)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 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/A5050175176","display_name":"Lit-Yang Liew","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Lit-Yang Liew","raw_affiliation_strings":["National Taiwan University,College of Electrical Engineering and Computer Science,Department of Electrical Engineering,Taipei,Taiwan R.O.C","Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan R.O.C"],"affiliations":[{"raw_affiliation_string":"National Taiwan University,College of Electrical Engineering and Computer Science,Department of Electrical Engineering,Taipei,Taiwan R.O.C","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan R.O.C","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019090684","display_name":"Sheng\u2010De Wang","orcid":"https://orcid.org/0000-0001-8856-7850"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Sheng-De Wang","raw_affiliation_strings":["National Taiwan University,College of Electrical Engineering and Computer Science,Department of Electrical Engineering,Taipei,Taiwan R.O.C","Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan R.O.C"],"affiliations":[{"raw_affiliation_string":"National Taiwan University,College of Electrical Engineering and Computer Science,Department of Electrical Engineering,Taipei,Taiwan R.O.C","institution_ids":["https://openalex.org/I16733864"]},{"raw_affiliation_string":"Department of Electrical Engineering, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan R.O.C","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050175176"],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.1799,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.47518893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9983000159263611,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/computer-science","display_name":"Computer science","score":0.8629360795021057},{"id":"https://openalex.org/keywords/multiprocessing","display_name":"Multiprocessing","score":0.5184816718101501},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5015332698822021},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4466526210308075},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.4449123740196228},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42755916714668274},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.4095335006713867},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.38046783208847046},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.35586169362068176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2741681933403015},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.23361808061599731},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.1237211525440216}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8629360795021057},{"id":"https://openalex.org/C4822641","wikidata":"https://www.wikidata.org/wiki/Q846651","display_name":"Multiprocessing","level":2,"score":0.5184816718101501},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5015332698822021},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4466526210308075},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.4449123740196228},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42755916714668274},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.4095335006713867},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.38046783208847046},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35586169362068176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2741681933403015},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.23361808061599731},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.1237211525440216}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce53296.2022.9730159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce53296.2022.9730159","pdf_url":null,"source":{"id":"https://openalex.org/S4363608007","display_name":"2022 IEEE International Conference on Consumer Electronics (ICCE)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Consumer Electronics (ICCE)","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":0.8899999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2260663238","https://openalex.org/W2300242332","https://openalex.org/W2707890836","https://openalex.org/W2764043458","https://openalex.org/W2886014761","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963122961","https://openalex.org/W3018757597","https://openalex.org/W3111800908","https://openalex.org/W3180134609","https://openalex.org/W4293584584","https://openalex.org/W6692521979","https://openalex.org/W6698200048","https://openalex.org/W6726275242","https://openalex.org/W6739917289","https://openalex.org/W6745148473","https://openalex.org/W6746698991","https://openalex.org/W6750227808","https://openalex.org/W6753645039","https://openalex.org/W6777046832","https://openalex.org/W6785808489"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W4200391368","https://openalex.org/W2210979487","https://openalex.org/W2074043759","https://openalex.org/W3042736233","https://openalex.org/W2082487009","https://openalex.org/W1967938402","https://openalex.org/W2386041993","https://openalex.org/W1608572506","https://openalex.org/W2160474882"],"abstract_inverted_index":{"Object":[0],"detection":[1,103,122,135,155],"tasks":[2],"implemented":[3],"using":[4],"complex":[5,157],"convolutional":[6],"neural":[7],"network":[8,116],"(CNN)":[9],"algorithms":[10],"are":[11],"both":[12],"computational":[13],"and":[14,48,55,96],"memory":[15],"intensive,":[16],"making":[17],"them":[18],"difficult":[19],"to":[20,27,39,70,152],"deploy":[21],"on":[22,106,108],"CPU-only":[23],"embedded":[24],"systems":[25,35,44],"due":[26],"their":[28],"limited":[29],"edge":[30,146],"computing":[31,150],"capabilities.":[32],"Heterogeneous":[33],"multiprocessor":[34,112],"come":[36],"in":[37,99,133],"handy":[38],"perform":[40,71],"these":[41],"tasks.":[42],"These":[43],"usually":[45],"integrate":[46],"CPU":[47],"other":[49],"processing":[50],"units":[51],"like":[52],"GPU,":[53],"DSP":[54],"FPGA":[56],"such":[57,90],"that":[58,67,72,140],"each":[59],"task":[60,73,104],"is":[61,68,118,125],"preferably":[62],"executed":[63],"by":[64],"the":[65,119],"unit":[66],"able":[69],"efficiently":[74],"with":[75,84,148,156],"superior":[76],"energy":[77],"efficiency.":[78],"This":[79],"paper":[80],"proposes":[81],"a":[82,85,109,144],"workflow":[83],"series":[86],"of":[87],"optimization":[88],"approaches":[89],"as":[91],"model":[92,94],"pruning,":[93],"quantization":[95],"multi-threading":[97],"design":[98],"implementing":[100],"an":[101],"object":[102,134,154],"based":[105],"YOLOv4-CSP":[107,115],"FPGA-based":[110],"heterogeneous":[111],"system.":[113],"The":[114,137],"architecture":[117],"state-of-the-art":[120],"one-stage":[121],"model.":[123],"It":[124],"widely":[126],"known":[127],"for":[128],"its":[129],"fast":[130],"inference":[131],"time":[132],"task.":[136],"experiments":[138],"show":[139],"we":[141],"can":[142],"achieve":[143],"significant":[145],"performance":[147],"lesser":[149],"resources":[151],"implement":[153],"CNN":[158],"algorithms.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
