{"id":"https://openalex.org/W3031146573","doi":"https://doi.org/10.1109/access.2020.2997033","title":"Deep Neural Network-Based In-Vehicle People Localization Using Ultra-Wideband Radar","display_name":"Deep Neural Network-Based In-Vehicle People Localization Using Ultra-Wideband Radar","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3031146573","doi":"https://doi.org/10.1109/access.2020.2997033","mag":"3031146573"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2997033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09099240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09099240.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052308555","display_name":"Sohee Lim","orcid":"https://orcid.org/0000-0002-4340-4545"},"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"]},{"id":"https://openalex.org/I4210164379","display_name":"Seoul Media Institute of Technology","ror":"https://ror.org/04ywg4h07","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210164379"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sohee Lim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I4210164379"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087873340","display_name":"Jaehoon Jung","orcid":"https://orcid.org/0000-0002-9562-6828"},"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"]},{"id":"https://openalex.org/I4210164379","display_name":"Seoul Media Institute of Technology","ror":"https://ror.org/04ywg4h07","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210164379"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehoon Jung","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I4210164379"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100745874","display_name":"Seong-Cheol Kim","orcid":"https://orcid.org/0000-0002-7896-5625"},"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"]},{"id":"https://openalex.org/I4210164379","display_name":"Seoul Media Institute of Technology","ror":"https://ror.org/04ywg4h07","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210164379"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Cheol Kim","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-7896-5625","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Institute of New Media and Communications (INMC), College of Engineering, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467","https://openalex.org/I4210164379"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021529299","display_name":"Seongwook Lee","orcid":"https://orcid.org/0000-0001-9115-4897"},"institutions":[{"id":"https://openalex.org/I24456540","display_name":"Korea Aerospace University","ror":"https://ror.org/05jmm0651","country_code":"KR","type":"education","lineage":["https://openalex.org/I24456540"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongwook Lee","raw_affiliation_strings":["School of Electronics and Information Engineering, College of Engineering, Korea Aerospace University, Gyeonggi-do, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9115-4897","affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, College of Engineering, Korea Aerospace University, Gyeonggi-do, South Korea","institution_ids":["https://openalex.org/I24456540"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":1.2837,"has_fulltext":true,"cited_by_count":33,"citation_normalized_percentile":{"value":0.77195355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"96606","last_page":"96612"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.994700014591217,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.7938982248306274},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6604487299919128},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.635734498500824},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6235561966896057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6219273209571838},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5371295809745789},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49366602301597595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45937100052833557},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4448099434375763},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4212372303009033},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1470586359500885}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7938982248306274},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6604487299919128},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.635734498500824},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6235561966896057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6219273209571838},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5371295809745789},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49366602301597595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45937100052833557},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4448099434375763},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4212372303009033},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1470586359500885}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2997033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09099240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:94702cb8902244228d31622c3266d1ba","is_oa":true,"landing_page_url":"https://doaj.org/article/94702cb8902244228d31622c3266d1ba","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 96606-96612 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2997033","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997033","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09099240.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G3701002343","display_name":null,"funder_award_id":"2019R1A2C2086621","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G5449412090","display_name":null,"funder_award_id":"2019R1A2C2086621","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G835851958","display_name":null,"funder_award_id":"2019R1A2C2086621","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3031146573.pdf","grobid_xml":"https://content.openalex.org/works/W3031146573.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1489213086","https://openalex.org/W1554944419","https://openalex.org/W1605688901","https://openalex.org/W1645981270","https://openalex.org/W1983259851","https://openalex.org/W1993192093","https://openalex.org/W2014815679","https://openalex.org/W2030107550","https://openalex.org/W2052770734","https://openalex.org/W2071878275","https://openalex.org/W2119047737","https://openalex.org/W2119821739","https://openalex.org/W2132804278","https://openalex.org/W2139670260","https://openalex.org/W2140556172","https://openalex.org/W2166946383","https://openalex.org/W2171033594","https://openalex.org/W2410591237","https://openalex.org/W2606735756","https://openalex.org/W2789436454","https://openalex.org/W2888801562","https://openalex.org/W2945035621","https://openalex.org/W2962781578","https://openalex.org/W2997966405","https://openalex.org/W3013360690","https://openalex.org/W4239510810","https://openalex.org/W6679703827","https://openalex.org/W6684636151"],"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/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W4224922629"],"abstract_inverted_index":{"In":[0,110],"this":[1],"paper,":[2],"we":[3,54,83,112],"present":[4],"an":[5,25,157],"in-vehicle":[6],"people":[7,47,155],"localization":[8],"technique":[9],"using":[10],"a":[11,60,66,77,178],"deep":[12],"neural":[13],"network":[14,78],"(DNN)":[15],"model":[16],"that":[17,169],"is":[18,32,68,168,171],"trained":[19],"by":[20,42,87],"the":[21,35,44,51,56,85,89,94,99,108,114,117,139,150,162],"experimental":[22],"data.":[23],"First,":[24],"impulse":[26],"radio":[27],"ultra-wide":[28],"band":[29],"(IR-UWB)":[30],"radar":[31,180],"installed":[33],"inside":[34],"vehicle,":[36],"and":[37,98,131,152],"received":[38],"signals":[39],"are":[40],"acquired":[41,52],"changing":[43,88],"arrangement":[45],"of":[46,91,96,101,107,116,154,159,164],"sitting.":[48],"Then,":[49],"on":[50],"data,":[53],"apply":[55],"DNN":[57],"to":[58,149,174],"train":[59],"classifier,":[61],"which":[62],"can":[63,143],"predict":[64],"whether":[65],"person":[67],"sitting":[69],"or":[70],"not":[71],"in":[72,103],"each":[73,104],"seat.":[74],"To":[75],"design":[76],"suitable":[79],"for":[80],"our":[81,136,165],"system,":[82],"evaluate":[84],"performance":[86,115],"type":[90],"activation":[92],"function,":[93],"number":[95,100,153],"layers,":[97],"nodes":[102],"hidden":[105],"layer":[106],"DNN.":[109],"addition,":[111],"compare":[113],"proposed":[118,140,166],"method":[119,142,167],"with":[120,156],"conventional":[121],"machine":[122,129],"learning":[123],"algorithms":[124],"such":[125],"as":[126],"support":[127],"vector":[128],"(SVM)":[130],"decision":[132],"tree-based":[133],"methods.":[134],"From":[135],"measured":[137],"signals,":[138],"DNN-based":[141],"classify":[144],"all":[145],"possible":[146],"cases":[147],"according":[148],"location":[151],"accuracy":[158],"99%.":[160],"Moreover,":[161],"advantage":[163],"there":[170],"no":[172],"need":[173],"extract":[175],"features":[176],"from":[177],"given":[179],"signal.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}