{"id":"https://openalex.org/W4412151703","doi":"https://doi.org/10.32604/cmc.2025.065525","title":"A Quality of Service Analysis of FPGA-Accelerated Conv2D Architectures for Brain Tumor Multi-Classification","display_name":"A Quality of Service Analysis of FPGA-Accelerated Conv2D Architectures for Brain Tumor Multi-Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412151703","doi":"https://doi.org/10.32604/cmc.2025.065525"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.065525","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065525","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.065525","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030186848","display_name":"Ayoub Mhaouch","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ayoub Mhaouch","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056995426","display_name":"Wafa Gtifa","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wafa Gtifa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091807777","display_name":"Turke Althobaiti","orcid":"https://orcid.org/0000-0002-6674-7890"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Turke Althobaiti","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095771936","display_name":"Hamzah Faraj","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hamzah Faraj","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5066475844","display_name":"Mohsen Machhout","orcid":"https://orcid.org/0000-0002-5629-0508"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohsen Machhout","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030186848"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7048,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.85500647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"84","issue":"3","first_page":"5637","last_page":"5663"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.958299994468689,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9559000134468079,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6529613733291626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.557014524936676},{"id":"https://openalex.org/keywords/brain-tumor","display_name":"Brain tumor","score":0.46406230330467224},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.43637901544570923},{"id":"https://openalex.org/keywords/service-quality","display_name":"Service quality","score":0.4346764087677002},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.42302244901657104},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.39815208315849304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38571897149086},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3394858241081238},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33106714487075806},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2497364580631256},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1927361786365509},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.11881527304649353},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09554839134216309}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6529613733291626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.557014524936676},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.46406230330467224},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.43637901544570923},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.4346764087677002},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42302244901657104},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.39815208315849304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38571897149086},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3394858241081238},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33106714487075806},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2497364580631256},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1927361786365509},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.11881527304649353},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09554839134216309},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.065525","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065525","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.065525","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065525","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials & Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2604319603","https://openalex.org/W2790729248","https://openalex.org/W2901364394","https://openalex.org/W2909533222","https://openalex.org/W3000396774","https://openalex.org/W3012561096","https://openalex.org/W3041090558","https://openalex.org/W3084741591","https://openalex.org/W3089472426","https://openalex.org/W3136154048","https://openalex.org/W3163071387","https://openalex.org/W3197665962","https://openalex.org/W3211740276","https://openalex.org/W4200370950","https://openalex.org/W4200604594","https://openalex.org/W4310289750","https://openalex.org/W4312222252","https://openalex.org/W4360864690","https://openalex.org/W4392796680","https://openalex.org/W4393353258","https://openalex.org/W4395464219","https://openalex.org/W4401877518","https://openalex.org/W4402039234","https://openalex.org/W4406778730"],"related_works":["https://openalex.org/W2111241003","https://openalex.org/W2355315220","https://openalex.org/W4200391368","https://openalex.org/W2096844293","https://openalex.org/W2363944576","https://openalex.org/W2351041855","https://openalex.org/W2570254841","https://openalex.org/W1967938402","https://openalex.org/W2386041993","https://openalex.org/W1608572506"],"abstract_inverted_index":{"In":[0,35],"medical":[1,8,118,234],"imaging,":[2],"accurate":[3],"brain":[4,47,225],"tumor":[5,226],"classification":[6,188],"in":[7,117,130,157,205,232],"imaging":[9,235],"requires":[10],"real-time":[11,143],"processing":[12],"and":[13,27,72,132,144,170,201,208,223],"efficient":[14],"computation,":[15],"making":[16,29,139],"hardware":[17,115,209],"acceleration":[18,91,116,219],"essential.":[19],"Field":[20],"Programmable":[21],"Gate":[22],"Arrays":[23],"(FPGAs)":[24],"offer":[25],"parallelism":[26],"reconfigurability,":[28],"them":[30],"well-suited":[31],"for":[32,46,114,142,220],"such":[33],"tasks.":[34],"this":[36],"study,":[37],"we":[38],"propose":[39],"a":[40,127,149,154,192],"hardware-accelerated":[41],"Convolutional":[42],"Neural":[43],"Network":[44],"(CNN)":[45],"cancer":[48],"classification,":[49,227],"implemented":[50],"on":[51,81],"the":[52,58,77,94,105,110,121,124,180,186,214],"PYNQ-Z2":[53,122],"FPGA.":[54],"Our":[55],"approach":[56],"optimizes":[57],"first":[59],"Conv2D":[60],"layer":[61],"using":[62],"different":[63],"numerical":[64,112],"representations:":[65],"8-bit":[66],"fixed-point":[67,70,74],"(INT8),":[68],"16-bit":[69],"(FP16),":[71],"32-bit":[73],"(FP32),":[75],"while":[76,165],"remaining":[78],"layers":[79],"run":[80],"an":[82],"ARM":[83],"Cortex-A9":[84],"processor.":[85],"Experimental":[86],"results":[87,103],"demonstrate":[88,213],"that":[89],"FPGA":[90],"significantly":[92],"outperforms":[93],"CPU":[95,203],"(Central":[96],"Processing":[97],"Unit)":[98],"based":[99],"approach.":[100],"The":[101],"obtained":[102],"emphasize":[104],"critical":[106],"importance":[107],"of":[108,194,216],"selecting":[109],"appropriate":[111],"representation":[113],"imaging.":[119],"On":[120],"FPGA,":[123],"INT8":[125],"achieves":[126,185],"16.8%":[128],"reduction":[129],"latency":[131,167],"22.2%":[133],"power":[134,172],"savings":[135],"compared":[136,159],"to":[137,160,177,196],"FP32,":[138],"it":[140],"ideal":[141],"energy-constrained":[145],"applications.":[146],"FP16":[147],"offers":[148],"strong":[150],"balance,":[151],"delivering":[152],"only":[153],"0.1%":[155],"drop":[156],"accuracy":[158,189,207],"FP32":[161],"(94.1%":[162],"vs.":[163],"94.2%)":[164],"improving":[166],"by":[168,174],"5%":[169],"reducing":[171],"consumption":[173],"11.1%.":[175],"Compared":[176],"prior":[178],"works,":[179],"proposed":[181],"FPGA-based":[182,217],"CNN":[183],"model":[184],"highest":[187],"(94.2%)":[190],"with":[191],"throughput":[193],"up":[195],"1.562":[197],"FPS,":[198],"outperforming":[199],"GPU-based":[200],"traditional":[202],"methods":[204],"both":[206],"efficiency.":[210],"These":[211],"findings":[212],"effectiveness":[215],"AI":[218],"real-time,":[221],"power-efficient,":[222],"high-performance":[224],"showcasing":[228],"its":[229],"practical":[230],"potential":[231],"next-generation":[233],"systems.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}