{"id":"https://openalex.org/W2897261990","doi":"https://doi.org/10.1145/3239576.3239609","title":"A Deep Learning Prediction Process Based on Low-power Heterogeneous Multi Core Architecture","display_name":"A Deep Learning Prediction Process Based on Low-power Heterogeneous Multi Core Architecture","publication_year":2018,"publication_date":"2018-06-16","ids":{"openalex":"https://openalex.org/W2897261990","doi":"https://doi.org/10.1145/3239576.3239609","mag":"2897261990"},"language":"en","primary_location":{"id":"doi:10.1145/3239576.3239609","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3239576.3239609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Advances in Image Processing","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/A5100448367","display_name":"Rui Li","orcid":"https://orcid.org/0000-0001-7858-3160"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Li","raw_affiliation_strings":["Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384525","display_name":"Da Li","orcid":"https://orcid.org/0000-0001-6822-3989"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Li","raw_affiliation_strings":["Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100379607","display_name":"Shuo Zhang","orcid":"https://orcid.org/0000-0002-0892-8642"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Zhang","raw_affiliation_strings":["Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center for IoT Software and Systems, Beijing University of Technology, Beijing, China, Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100448367"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.11694032,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"220","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9923999905586243,"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":0.9923999905586243,"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":0.9854999780654907,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7920643091201782},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.7829843163490295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6300142407417297},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6181991696357727},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5123559236526489},{"id":"https://openalex.org/keywords/multi-core-processor","display_name":"Multi-core processor","score":0.46533361077308655},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4652251899242401},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.4606783986091614},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4434516727924347},{"id":"https://openalex.org/keywords/arm-architecture","display_name":"ARM architecture","score":0.4348664879798889},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.32083749771118164},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.31226903200149536},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.20178493857383728},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10026785731315613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7920643091201782},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.7829843163490295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6300142407417297},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6181991696357727},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5123559236526489},{"id":"https://openalex.org/C78766204","wikidata":"https://www.wikidata.org/wiki/Q555032","display_name":"Multi-core processor","level":2,"score":0.46533361077308655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4652251899242401},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.4606783986091614},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4434516727924347},{"id":"https://openalex.org/C26771161","wikidata":"https://www.wikidata.org/wiki/Q16980","display_name":"ARM architecture","level":2,"score":0.4348664879798889},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.32083749771118164},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.31226903200149536},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.20178493857383728},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10026785731315613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3239576.3239609","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3239576.3239609","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Advances in Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1591178201","https://openalex.org/W2018814245","https://openalex.org/W2070167224","https://openalex.org/W2119055835","https://openalex.org/W2123965599","https://openalex.org/W2138634601","https://openalex.org/W2152839228","https://openalex.org/W2511309458","https://openalex.org/W2592549397"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W3012895752","https://openalex.org/W2389916899"],"abstract_inverted_index":{"With":[0],"the":[1,13,28,62,75,78,106,110,157,161,176,209,218],"rapid":[2],"development":[3],"of":[4,31,65,77,83,212],"machine":[5,32],"learning":[6,35,42,51,72],"both":[7],"in":[8,12,22,39,193],"theory":[9],"and":[10,24,90,109,130,160,199],"practice":[11],"past":[14],"decade.":[15],"And":[16],"recently,":[17],"it":[18],"is":[19],"widely":[20],"used":[21],"applications":[23],"cloud":[25],"services.":[26],"As":[27],"emerging":[29],"field":[30],"learning,":[33],"deep":[34,50,71],"shows":[36],"excellent":[37],"ability":[38],"solving":[40],"complex":[41],"problems.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47],"designed":[48],"a":[49,81],"prediction":[52],"process":[53,91],"based":[54,69,96,144,170],"on":[55,70,97,114,145,171],"low-power":[56],"heterogeneous":[57,134],"multi":[58,99,135],"core":[59,100,136,215],"architecture.":[60],"Firstly,":[61],"fundamental":[63],"principle":[64],"image":[66,92,151,178],"recognition":[67,152,158,179],"method":[68],"reviewed":[73],"as":[74,217],"basis":[76],"research.":[79],"Secondly,":[80],"set":[82],"key":[84,142],"algorithm":[85],"design":[86],"to":[87,104,149,155],"parallel":[88],"access":[89],"for":[93],"object":[94],"detection":[95,107],"Parallella":[98,146,172,194],"platform":[101,138],"was":[102,139,153,191],"proposed":[103,154,177],"improve":[105,156],"speed":[108,159],"computational":[111,162],"resource":[112,163],"efficiency":[113],"single":[115],"node.":[116],"Thirdly,":[117],"Rockchip":[118],"RK3288":[119,205],"SoC":[120],"with":[121,196],"4":[122,221],"Arm":[123,189,214,222],"Cortex-A17":[124,223],"cores":[125],"hardware":[126,137],"platform,":[127],"Xilinx":[128],"Zynq":[129],"Adapteva":[131],"Epiphany":[132],"combined":[133],"introduced.":[140],"Some":[141],"designs":[143],"board's":[147],"architecture":[148],"achieve":[150,182,200],"efficiency.":[164],"Finally,":[165],"The":[166],"experimental":[167],"results":[168],"that":[169,175],"board":[173,195,206],"indicate":[174],"system":[180],"can":[181],"nearly":[183],"14.8":[184],"times":[185,202],"speedup":[186,203],"than":[187,204],"dual-core":[188],"which":[190,207],"integrated":[192],"similar":[197],"accuracy":[198],"8.6":[201],"has":[208],"newest":[210],"series":[211],"high-performance":[213],"CPU":[216],"control":[219],"included":[220],"cores.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}