{"id":"https://openalex.org/W3027871700","doi":"https://doi.org/10.1109/les.2020.2996758","title":"Embedded Identification of Surface Based on Multirate Sensor Fusion With Deep Neural Network","display_name":"Embedded Identification of Surface Based on Multirate Sensor Fusion With Deep Neural Network","publication_year":2020,"publication_date":"2020-05-22","ids":{"openalex":"https://openalex.org/W3027871700","doi":"https://doi.org/10.1109/les.2020.2996758","mag":"3027871700"},"language":"en","primary_location":{"id":"doi:10.1109/les.2020.2996758","is_oa":true,"landing_page_url":"https://doi.org/10.1109/les.2020.2996758","pdf_url":"https://ieeexplore.ieee.org/ielx7/4563995/9442409/09098953.pdf","source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Embedded Systems Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/4563995/9442409/09098953.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053042064","display_name":"Semin Ryu","orcid":"https://orcid.org/0000-0002-4183-0014"},"institutions":[{"id":"https://openalex.org/I146824383","display_name":"Hallym University","ror":"https://ror.org/03sbhge02","country_code":"KR","type":"education","lineage":["https://openalex.org/I146824383"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Semin Ryu","raw_affiliation_strings":["Hallym Institute for Data Science and Artificial Intelligence, Hallym University, Chuncheon, South Korea","Intelligent Robotics Laboratory, Hallym University, Chuncheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4183-0014","affiliations":[{"raw_affiliation_string":"Hallym Institute for Data Science and Artificial Intelligence, Hallym University, Chuncheon, South Korea","institution_ids":["https://openalex.org/I146824383"]},{"raw_affiliation_string":"Intelligent Robotics Laboratory, Hallym University, Chuncheon, South Korea","institution_ids":["https://openalex.org/I146824383"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039793968","display_name":"Seung-Chan Kim","orcid":"https://orcid.org/0000-0001-7292-5166"},"institutions":[{"id":"https://openalex.org/I146824383","display_name":"Hallym University","ror":"https://ror.org/03sbhge02","country_code":"KR","type":"education","lineage":["https://openalex.org/I146824383"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung-Chan Kim","raw_affiliation_strings":["Hallym Institute for Data Science and Artificial Intelligence, Hallym University, Chuncheon, South Korea","Intelligent Robotics Laboratory, Hallym University, Chuncheon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-7292-5166","affiliations":[{"raw_affiliation_string":"Hallym Institute for Data Science and Artificial Intelligence, Hallym University, Chuncheon, South Korea","institution_ids":["https://openalex.org/I146824383"]},{"raw_affiliation_string":"Intelligent Robotics Laboratory, Hallym University, Chuncheon, South Korea","institution_ids":["https://openalex.org/I146824383"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0312,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.89429747,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"13","issue":"2","first_page":"49","last_page":"52"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8522101640701294},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6688071489334106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6551955342292786},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6001911163330078},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5663183927536011},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5060510039329529},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5034210085868835},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3379271328449249}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8522101640701294},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6688071489334106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6551955342292786},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6001911163330078},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5663183927536011},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5060510039329529},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5034210085868835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3379271328449249},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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/les.2020.2996758","is_oa":true,"landing_page_url":"https://doi.org/10.1109/les.2020.2996758","pdf_url":"https://ieeexplore.ieee.org/ielx7/4563995/9442409/09098953.pdf","source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Embedded Systems Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/les.2020.2996758","is_oa":true,"landing_page_url":"https://doi.org/10.1109/les.2020.2996758","pdf_url":"https://ieeexplore.ieee.org/ielx7/4563995/9442409/09098953.pdf","source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Embedded Systems Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4471639822","display_name":null,"funder_award_id":"2019-0-00050","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G6239084344","display_name":null,"funder_award_id":"HRF-201803-001","funder_id":"https://openalex.org/F4320321367","funder_display_name":"Hallym University"},{"id":"https://openalex.org/G6297514046","display_name":null,"funder_award_id":"2019-0-00050","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G8331172550","display_name":null,"funder_award_id":"2019-0-00050","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320321367","display_name":"Hallym University","ror":"https://ror.org/03sbhge02"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320324891","display_name":"Iran Telecommunication Research Center","ror":"https://ror.org/01a3g2z22"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3027871700.pdf","grobid_xml":"https://content.openalex.org/works/W3027871700.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1989234558","https://openalex.org/W1997244800","https://openalex.org/W2121364715","https://openalex.org/W2163605009","https://openalex.org/W2184188583","https://openalex.org/W2187089797","https://openalex.org/W2777460464","https://openalex.org/W2888248339","https://openalex.org/W2971680695","https://openalex.org/W2972418643","https://openalex.org/W6610017368","https://openalex.org/W6684191040","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4210874298","https://openalex.org/W2898732673"],"abstract_inverted_index":{"In":[0,24],"this":[1,129],"letter,":[2],"we":[3,83],"propose":[4],"a":[5,20,48,67,95,104,108,132],"multivariate":[6],"time-series":[7],"classification":[8,121],"system":[9,28,87],"that":[10],"fuses":[11],"multirate":[12],"sensor":[13],"measurements":[14,38],"within":[15],"the":[16,27,30,41,58,135],"latent":[17],"space":[18],"of":[19,45,60,97,112,134,140],"deep":[21],"neural":[22,70],"network.":[23],"our":[25,81],"network,":[26,71],"identifies":[29],"surface":[31,42],"category":[32],"based":[33],"on":[34],"audio":[35],"and":[36,52,88,137],"inertial":[37],"generated":[39],"from":[40],"impact,":[43],"each":[44],"which":[46,72],"has":[47],"different":[49,63],"sampling":[50],"rate":[51],"resolution":[53],"in":[54,75,122],"nature.":[55],"We":[56,127],"investigate":[57],"feasibility":[59],"categorizing":[61],"ten":[62],"everyday":[64],"surfaces":[65],"using":[66],"proposed":[68],"convolutional":[69],"is":[73],"trained":[74],"an":[76,85,123],"end-to-end":[77,120],"manner.":[78],"To":[79],"validate":[80],"approach,":[82],"developed":[84],"embedded":[86,124],"collected":[89],"60":[90],"000":[91],"data":[92],"samples":[93],"under":[94],"variety":[96],"conditions.":[98],"The":[99],"experimental":[100],"results":[101,136],"obtained":[102],"exhibit":[103],"test":[105,110],"accuracy":[106],"for":[107,119],"blind":[109],"dataset":[111],"93%,":[113],"taking":[114],"less":[115],"than":[116],"300":[117],"ms":[118],"machine":[125],"environment.":[126],"conclude":[128],"letter":[130],"with":[131],"discussion":[133],"future":[138],"direction":[139],"research.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
