{"id":"https://openalex.org/W2775223824","doi":"https://doi.org/10.1109/iccad.2017.8203864","title":"VoCaM: Visualization oriented convolutional neural network acceleration on mobile system: Invited paper","display_name":"VoCaM: Visualization oriented convolutional neural network acceleration on mobile system: Invited paper","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2775223824","doi":"https://doi.org/10.1109/iccad.2017.8203864","mag":"2775223824"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2017.8203864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203864","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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/A5018832267","display_name":"Zhuwei Qin","orcid":"https://orcid.org/0000-0002-5465-7740"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhuwei Qin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030027584","display_name":"Zirui Xu","orcid":"https://orcid.org/0000-0002-3556-9358"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zirui Xu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041310780","display_name":"Qide Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qide Dong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058073627","display_name":"Yiran Chen","orcid":"https://orcid.org/0000-0002-1486-8412"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiran Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100441957","display_name":"Xiang Chen","orcid":"https://orcid.org/0000-0003-2790-976X"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018832267"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13333333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1512","issue":null,"first_page":"835","last_page":"840"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9991999864578247,"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":0.9991999864578247,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9980999827384949,"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":0.9980000257492065,"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/computer-science","display_name":"Computer science","score":0.873443603515625},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7060186862945557},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6834749579429626},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5674392580986023},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5260933637619019},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.5168893337249756},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.49729612469673157},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4580674469470978},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4527398347854614},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45001450181007385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.873443603515625},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7060186862945557},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6834749579429626},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5674392580986023},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5260933637619019},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.5168893337249756},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.49729612469673157},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4580674469470978},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4527398347854614},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45001450181007385},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2017.8203864","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2017.8203864","pdf_url":null,"source":{"id":"https://openalex.org/S4363608376","display_name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1524680991","https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1935978687","https://openalex.org/W1973175507","https://openalex.org/W1997764866","https://openalex.org/W2001996312","https://openalex.org/W2019377328","https://openalex.org/W2060393849","https://openalex.org/W2063571473","https://openalex.org/W2083842231","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2110630640","https://openalex.org/W2112796928","https://openalex.org/W2119144962","https://openalex.org/W2133400794","https://openalex.org/W2153811040","https://openalex.org/W2163605009","https://openalex.org/W2186615578","https://openalex.org/W2209990155","https://openalex.org/W2293137312","https://openalex.org/W2532077617","https://openalex.org/W2604882796","https://openalex.org/W2612193523","https://openalex.org/W2613718673","https://openalex.org/W2963000224","https://openalex.org/W6620707391","https://openalex.org/W6631498818","https://openalex.org/W6640289440","https://openalex.org/W6684191040","https://openalex.org/W6725543821"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W4293226380","https://openalex.org/W3124914020","https://openalex.org/W2141033859","https://openalex.org/W2077542787","https://openalex.org/W2156434174","https://openalex.org/W2071701083","https://openalex.org/W2383687187","https://openalex.org/W2081517010","https://openalex.org/W2121496884"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"have":[4,48,65,78,167,176],"been":[5,49,66,79],"widely":[6],"investigated":[7],"as":[8],"some":[9],"of":[10,129,146,159,184,216],"the":[11,42,86,93,105,130,135,143,147,156,173,196,203,213,217,225],"most":[12],"promising":[13],"solution":[14],"for":[15,122],"various":[16],"computer":[17],"vision":[18],"tasks.":[19,125],"However,":[20],"CNNs":[21],"introduce":[22],"massive":[23],"computing":[24,31,60,89,186,204],"overhead":[25],"due":[26],"to":[27,92,141,190,194],"their":[28],"complex":[29],"network":[30],"flow,":[32],"resulting":[33],"in":[34,41],"significantly":[35,211],"reduced":[36],"applicability":[37],"and":[38,57,200],"performance,":[39],"especially":[40],"mobile":[43,106,120,131],"devices.":[44],"Various":[45],"optimization":[46,76],"schemes":[47,64],"proposed":[50],"mainly":[51],"based":[52],"on":[53,119,224],"both":[54],"model":[55],"compression":[56],"stacked":[58],"external":[59],"resources.":[61],"While":[62],"these":[63,191],"proven":[67],"effective,":[68],"methods":[69,187],"which":[70,99],"take":[71],"into":[72],"account":[73],"mobile-specific":[74],"context-aware":[75],"approaches":[77],"largely":[80],"overlooked.":[81],"One":[82],"such":[83],"opportunity":[84],"is":[85,188],"feasible":[87],"CNN":[88,116],"flow":[90],"simplification":[91],"under-test":[94,148,174],"objects":[95],"with":[96,220],"distinguish":[97],"features,":[98],"can":[100,138,210],"be":[101,139],"efficiently":[102],"pre-analyzed":[103],"inside":[104],"sensor":[107],"system.":[108],"Hence,":[109],"we":[110],"propose":[111],"VoCaM,":[112],"a":[113,182],"visualization":[114,157],"oriented":[115],"acceleration":[117],"framework":[118],"devices":[121],"image":[123],"classification":[124,227],"VoCaM":[126,160,209],"takes":[127],"advantage":[128],"camera":[132],"system,":[133],"where":[134],"comprehensive":[136],"pre-analysis":[137],"conducted":[140],"reveal":[142],"color":[144,179],"composition":[145],"images":[149,175],"without":[150],"incurring":[151],"any":[152],"additional":[153],"overhead.":[154],"Also,":[155],"analysis":[158],"reveals":[161],"that,":[162],"certain":[163],"color-specific":[164],"filters":[165,193],"may":[166],"very":[168,221],"trivial":[169],"result":[170],"impact":[171,223],"when":[172],"mismatching":[177],"primary":[178],"components.":[180],"Then":[181],"set":[183],"approximate":[185],"applied":[189],"insignificant":[192],"replace":[195],"intensive":[197],"convolutional":[198,218],"operation,":[199],"greatly":[201],"accelerate":[202],"process.":[205],"With":[206],"ignorable":[207],"overhead,":[208],"optimize":[212],"computation":[214],"load":[215],"layers,":[219],"small":[222],"overall":[226],"accuracy.":[228]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
