{"id":"https://openalex.org/W4220972674","doi":"https://doi.org/10.1109/icce53296.2022.9730557","title":"Accelerated SVM Algorithm for Sensors Fusion-based Activity Classification in Lightweighted Edge Devices","display_name":"Accelerated SVM Algorithm for Sensors Fusion-based Activity Classification in Lightweighted Edge Devices","publication_year":2022,"publication_date":"2022-01-07","ids":{"openalex":"https://openalex.org/W4220972674","doi":"https://doi.org/10.1109/icce53296.2022.9730557"},"language":"en","primary_location":{"id":"doi:10.1109/icce53296.2022.9730557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce53296.2022.9730557","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/A5010736319","display_name":"Juneseo Chang","orcid":"https://orcid.org/0000-0001-7547-8349"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Juneseo Chang","raw_affiliation_strings":["Seoul National University,Department of Computer Science and Engineering,Seoul,Republic of Korea","Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Computer Science and Engineering,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049472656","display_name":"Myeongjin Kang","orcid":"https://orcid.org/0009-0008-4784-5517"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Myeongjin Kang","raw_affiliation_strings":["School of Electronics Engineering, Kyungpook National University,Daegu,Republic of Korea","School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University,Daegu,Republic of Korea","institution_ids":["https://openalex.org/I31419693"]},{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030304824","display_name":"Daejin Park","orcid":"https://orcid.org/0000-0002-5560-873X"},"institutions":[{"id":"https://openalex.org/I31419693","display_name":"Kyungpook National University","ror":"https://ror.org/040c17130","country_code":"KR","type":"education","lineage":["https://openalex.org/I31419693"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daejin Park","raw_affiliation_strings":["School of Electronics Engineering, Kyungpook National University,Daegu,Republic of Korea","School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University,Daegu,Republic of Korea","institution_ids":["https://openalex.org/I31419693"]},{"raw_affiliation_string":"School of Electronics Engineering, Kyungpook National University, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I31419693"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010736319"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.432,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.42547275,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"abs 2010 8678","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9872999787330627,"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"}},"topics":[{"id":"https://openalex.org/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9872999787330627,"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"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9868000149726868,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7332106828689575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6667695045471191},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6126105189323425},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5769961476325989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5287801027297974},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49266868829727173},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.49107980728149414},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4721907377243042},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40570738911628723}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7332106828689575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6667695045471191},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6126105189323425},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5769961476325989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5287801027297974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49266868829727173},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.49107980728149414},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4721907377243042},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40570738911628723},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce53296.2022.9730557","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce53296.2022.9730557","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":"Decent work and economic growth","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G1914882398","display_name":null,"funder_award_id":"NRF-2018R1A6A1A03025109,10%","funder_id":"https://openalex.org/F4320311649","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1511019258","https://openalex.org/W2156385131","https://openalex.org/W3011347095","https://openalex.org/W3197985169","https://openalex.org/W4239035626","https://openalex.org/W4287639545","https://openalex.org/W6774875199","https://openalex.org/W6784225549"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"Smart":[0],"homes":[1],"assist":[2],"users":[3],"by":[4,119,134,158],"providing":[5],"convenient":[6],"services":[7],"from":[8,177],"human":[9],"activity":[10,60,69,84],"classification":[11,130,164],"with":[12],"the":[13,23,76,105,129,136,139,146,180],"help":[14],"of":[15,22,91,104,125],"machine":[16,175],"learning":[17],"(ML)":[18],"technology.":[19],"However,":[20],"most":[21],"conventional":[24],"high-performance":[25],"ML":[26,55,88],"algorithms":[27],"require":[28],"high":[29],"computing":[30],"power":[31],"and":[32,97,121,142,162,192],"memory":[33,187],"usage.":[34],"Therefore,":[35],"they":[36],"are":[37,108],"inapplicable":[38],"for":[39,57,67,82],"resource-limited":[40],"embedded":[41],"systems":[42],"such":[43],"as":[44,71,79],"smart":[45,58],"homes.":[46],"In":[47,99],"this":[48],"study,":[49],"we":[50],"propose":[51,64],"a":[52,65,80,171],"memory-efficient,":[53],"high-speed":[54],"algorithm":[56,89,153,182],"home":[59],"data":[61,70,94,100,103,141],"classification.":[62,98],"We":[63,150],"method":[66],"comprehending":[68],"image":[72],"data,":[73],"thereby":[74],"using":[75,145],"MNIST":[77],"dataset":[78],"substitute":[81],"real-world":[83],"data.":[85,127,168],"The":[86,114],"proposed":[87,181],"consists":[90],"three":[92],"parts:":[93],"preprocessing,":[95,101],"training,":[96],"training":[102,115,167],"same":[106],"label":[107],"grouped":[109],"into":[110],"further":[111],"detailed":[112],"clusters.":[113],"process":[116,131],"generates":[117],"hyperplanes":[118,161],"accumulating":[120],"thresholding":[122],"each":[123,143],"cluster":[124],"preprocessed":[126],"Finally,":[128],"is":[132],"done":[133],"calculating":[135],"similarity":[137],"between":[138],"input":[140],"hyperplane":[144],"bitwise-operation-based":[147],"error":[148],"function.":[149],"verified":[151],"our":[152],"on":[154,165],"‘Raspberry":[155],"Pi":[156],"3’":[157],"loading":[159],"trained":[160],"performing":[163],"1,000":[166],"Compared":[169],"to":[170,185,189,197],"linear":[172],"support":[173],"vector":[174],"implemented":[176],"Tensorflow":[178],"Lite,":[179],"improved":[183],"performance":[184],"45%,":[186],"usage":[188],"15.41":[190],"%,":[191],"execution":[193],"time":[194],"per":[195],"accuracy":[196],"41.3%.":[198]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}