{"id":"https://openalex.org/W7140641708","doi":"https://doi.org/10.1109/fpl68686.2025.00054","title":"Energy-Efficient DNNs on FPGAs for Edge-Cloud Computer Vision","display_name":"Energy-Efficient DNNs on FPGAs for Edge-Cloud Computer Vision","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W7140641708","doi":"https://doi.org/10.1109/fpl68686.2025.00054"},"language":null,"primary_location":{"id":"doi:10.1109/fpl68686.2025.00054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl68686.2025.00054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 35th International Conference on Field-Programmable Logic and Applications (FPL)","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/A5082966937","display_name":"Qaisar Farooq","orcid":"https://orcid.org/0000-0002-8645-3136"},"institutions":[{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Qaisar Farooq","raw_affiliation_strings":["Università di Torino,Turin,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Università di Torino,Turin,Italy","institution_ids":["https://openalex.org/I55143463"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077745494","display_name":"Id\u00edlio Drago","orcid":"https://orcid.org/0000-0003-1932-1261"},"institutions":[{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Idilio Drago","raw_affiliation_strings":["Università di Torino,Turin,Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Università di Torino,Turin,Italy","institution_ids":["https://openalex.org/I55143463"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5082966937"],"corresponding_institution_ids":["https://openalex.org/I55143463"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71814075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.3181999921798706,"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":0.3181999921798706,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.1615000069141388,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.08749999850988388,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.3991999924182892},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3580999970436096},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.3578000068664551},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2930000126361847},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2912999987602234}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6791999936103821},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5231999754905701},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49970000982284546},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.3991999924182892},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.26260000467300415},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fpl68686.2025.00054","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fpl68686.2025.00054","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 35th International Conference on Field-Programmable Logic and Applications (FPL)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8363708257675171,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W4313069943","https://openalex.org/W4404788843","https://openalex.org/W4411575788","https://openalex.org/W7133183521"],"related_works":[],"abstract_inverted_index":{"This":[0],"research":[1],"addresses":[2],"the":[3,140],"energy-efficient":[4],"deployment":[5,55],"of":[6,70,76,81,93],"deep":[7],"neural":[8,24],"networks":[9,83,95],"(DNNs)":[10],"on":[11,60,87,124,139,148],"FPGAs":[12],"for":[13,37],"edge-cloud":[14],"computer":[15],"vision":[16],"applications.":[17],"We":[18,100],"evaluate":[19],"and":[20,29,53,90,111],"compare":[21],"classic":[22],"convolutional":[23],"networks,":[25],"Vision":[26],"Transformers":[27],"(ViTs),":[28],"alternative":[30,98],"approaches":[31],"that":[32,120,130],"may":[33],"be":[34],"more":[35],"suitable":[36],"FPGA":[38,77],"deployment,":[39],"such":[40],"as":[41,96],"differentiable":[42],"boolean":[43],"logic":[44],"(DiffLogic)":[45],"networks.":[46],"Our":[47],"methodology":[48],"employs":[49],"hardware-aware":[50],"quantization":[51],"techniques":[52],"specialized":[54],"frameworks":[56],"to":[57],"optimize":[58],"performance":[59],"resource-constrained":[61],"systems.":[62],"The":[63],"expected":[64],"contributions":[65],"include:":[66],"i)":[67],"energy":[68],"characterization":[69],"DNN":[71],"accelerators,":[72],"ii)":[73],"comparative":[74],"analysis":[75],"toolchains,":[78],"iii)":[79],"optimization":[80],"modern":[82],"with":[84,143],"a":[85,112,149],"focus":[86],"attention":[88],"mechanisms,":[89],"iv)":[91],"evaluation":[92],"DiffLogic":[94],"an":[97],"architecture.":[99],"demonstrate":[101],"our":[102,131],"approach":[103],"through":[104],"both":[105],"toy":[106],"cases":[107],"(e.g.,":[108],"MNIST":[109],"dataset)":[110],"realistic":[113],"Driver":[114],"Distraction":[115],"Detection":[116],"(DDD)":[117],"case":[118],"study":[119],"requires":[121],"real-time":[122],"execution":[123],"edge":[125],"devices.":[126],"Preliminary":[127],"results":[128],"show":[129],"optimized":[132],"model":[133],"achieves":[134],"66":[135],"%":[136],"test":[137],"accuracy":[138],"DDD":[141],"problem":[142],"very":[144],"low":[145],"power":[146],"consumption":[147],"PYNQ-Z2":[150],"board.":[151]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-27T00:00:00"}