{"id":"https://openalex.org/W4223451968","doi":"https://doi.org/10.1109/iceic54506.2022.9748776","title":"FMCW Radar Sensor Based Human Activity Recognition using Deep Learning","display_name":"FMCW Radar Sensor Based Human Activity Recognition using Deep Learning","publication_year":2022,"publication_date":"2022-02-06","ids":{"openalex":"https://openalex.org/W4223451968","doi":"https://doi.org/10.1109/iceic54506.2022.9748776"},"language":"en","primary_location":{"id":"doi:10.1109/iceic54506.2022.9748776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic54506.2022.9748776","pdf_url":null,"source":{"id":"https://openalex.org/S4363608213","display_name":"2022 International Conference on Electronics, Information, and Communication (ICEIC)","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 International Conference on Electronics, Information, and Communication (ICEIC)","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/A5006006643","display_name":"Shahzad Ahmed","orcid":"https://orcid.org/0000-0002-4661-2956"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Shahzad Ahmed","raw_affiliation_strings":["Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020565526","display_name":"Junbyung Park","orcid":null},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junbyung Park","raw_affiliation_strings":["Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021420311","display_name":"Sung Ho Cho","orcid":"https://orcid.org/0000-0002-2393-1428"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung Ho Cho","raw_affiliation_strings":["Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Hanyang University,Dept. of Electronic Engineering,Seoul,South Korea","institution_ids":["https://openalex.org/I4575257"]},{"raw_affiliation_string":"Dept. of Electronic Engineering, Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006006643"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":null,"apc_paid":null,"fwci":7.713,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.98445987,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9995999932289124,"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":0.9995999932289124,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9746999740600586,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7831681966781616},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.7666096091270447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6861244440078735},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6728132367134094},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6135052442550659},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5203049182891846},{"id":"https://openalex.org/keywords/continuous-wave-radar","display_name":"Continuous-wave radar","score":0.5149715542793274},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.49129432439804077},{"id":"https://openalex.org/keywords/radar-engineering-details","display_name":"Radar engineering details","score":0.490788072347641},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47995996475219727},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.47057315707206726},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46567413210868835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4381949007511139},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.3291703462600708},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19969075918197632}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7831681966781616},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.7666096091270447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6861244440078735},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6728132367134094},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6135052442550659},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5203049182891846},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.5149715542793274},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.49129432439804077},{"id":"https://openalex.org/C134406370","wikidata":"https://www.wikidata.org/wiki/Q832005","display_name":"Radar engineering details","level":4,"score":0.490788072347641},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47995996475219727},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.47057315707206726},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46567413210868835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4381949007511139},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.3291703462600708},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19969075918197632},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceic54506.2022.9748776","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceic54506.2022.9748776","pdf_url":null,"source":{"id":"https://openalex.org/S4363608213","display_name":"2022 International Conference on Electronics, Information, and Communication (ICEIC)","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 International Conference on Electronics, Information, and Communication (ICEIC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2059732136","https://openalex.org/W2062950526","https://openalex.org/W2182211519","https://openalex.org/W2242223225","https://openalex.org/W2568698092","https://openalex.org/W2802040095","https://openalex.org/W2886300352","https://openalex.org/W2923491365","https://openalex.org/W2972240361","https://openalex.org/W2999165370","https://openalex.org/W3017078789","https://openalex.org/W3127000115","https://openalex.org/W3150907257","https://openalex.org/W3172752427","https://openalex.org/W3204207455","https://openalex.org/W6768272962"],"related_works":["https://openalex.org/W2142793224","https://openalex.org/W4380451819","https://openalex.org/W4296425733","https://openalex.org/W2892233029","https://openalex.org/W4285814362","https://openalex.org/W4352982730","https://openalex.org/W2027415419","https://openalex.org/W2103897432","https://openalex.org/W604796468","https://openalex.org/W2158590228"],"abstract_inverted_index":{"Human":[0],"Activity":[1],"Recognition":[2],"(HAR)":[3],"has":[4],"found":[5],"many":[6],"applications":[7],"in":[8,53],"several":[9],"disciplines":[10],"such":[11],"as":[12,104],"smart":[13],"home":[14],"and":[15,68,83,117],"elderly":[16],"healthcare":[17],"units.":[18],"The":[19,91],"robustness":[20],"of":[21,112,126],"radar":[22,48,67,82],"sensor":[23],"against":[24],"the":[25,98,108],"environmental":[26],"conditions":[27],"make":[28],"it":[29],"a":[30,69,84,118],"suitable":[31],"candidate":[32],"to":[33,107],"recognize":[34],"human":[35,51,100],"activities.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"used":[41,88],"Frequency":[42],"Modulated":[43],"Continuous":[44],"Wave":[45],"Radar":[46],"(FMCW)":[47],"for":[49,89],"recog-nizing":[50],"activities":[52,59],"an":[54,105],"unconstrained":[55],"environment.":[56],"Seven":[57],"different":[58,64],"are":[60,77,102],"performed":[61],"randomly":[62],"at":[63],"distances":[65],"from":[66],"multi-class":[70],"classification":[71,120],"problem":[72],"is":[73,87,121,128],"formulated.":[74],"Performed":[75],"activates":[76,101],"recorded":[78],"with":[79],"single":[80],"FMCW":[81],"deep-learning":[85],"classifier":[86],"recognition.":[90],"target":[92],"range":[93],"variations":[94],"generated":[95],"while":[96],"performing":[97],"predefined":[99],"fed":[103],"input":[106],"features":[109],"extraction":[110],"block":[111],"three":[113],"Convolutional":[114],"Neural":[115],"Network":[116],"softmax":[119],"performed.":[122],"Overall":[123],"recognition":[124],"accuracy":[125],"91%":[127],"achieved.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}