{"id":"https://openalex.org/W3004500412","doi":"https://doi.org/10.1109/access.2020.2971064","title":"A Hybrid CNN\u2013LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar","display_name":"A Hybrid CNN\u2013LSTM Network for the Classification of Human Activities Based on Micro-Doppler Radar","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3004500412","doi":"https://doi.org/10.1109/access.2020.2971064","mag":"3004500412"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2971064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971064","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08978926.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/ielx7/6287639/8948470/08978926.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036372234","display_name":"Jianping Zhu","orcid":"https://orcid.org/0000-0001-5160-6991"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Zhu","raw_affiliation_strings":["College of Electronic and Information Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100734403","display_name":"Haiquan Chen","orcid":"https://orcid.org/0000-0002-3039-5328"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiquan Chen","raw_affiliation_strings":["College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101960498","display_name":"Wenbin Ye","orcid":"https://orcid.org/0000-0001-6978-813X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Ye","raw_affiliation_strings":["College of Electronic and Information Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6978-813X","affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.7057,"has_fulltext":true,"cited_by_count":162,"citation_normalized_percentile":{"value":0.98667456,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"24713","last_page":"24720"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9993000030517578,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9894000291824341,"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/spectrogram","display_name":"Spectrogram","score":0.937018632888794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7670377492904663},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7236256003379822},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6770176887512207},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6714143753051758},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5805415511131287},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5542089343070984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5497836470603943},{"id":"https://openalex.org/keywords/doppler-radar","display_name":"Doppler radar","score":0.4479040801525116},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.42869019508361816},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41880369186401367},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.38230809569358826},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08747434616088867},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.08138418197631836},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07692179083824158}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.937018632888794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7670377492904663},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7236256003379822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6770176887512207},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6714143753051758},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5805415511131287},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5542089343070984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5497836470603943},{"id":"https://openalex.org/C2778559676","wikidata":"https://www.wikidata.org/wiki/Q1334213","display_name":"Doppler radar","level":3,"score":0.4479040801525116},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.42869019508361816},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41880369186401367},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.38230809569358826},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08747434616088867},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.08138418197631836},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07692179083824158},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2971064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971064","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08978926.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:a523a04984a3476faeaea8509e9cef75","is_oa":true,"landing_page_url":"https://doaj.org/article/a523a04984a3476faeaea8509e9cef75","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 24713-24720 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2971064","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2971064","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08978926.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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3004500412.pdf","grobid_xml":"https://content.openalex.org/works/W3004500412.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W648098667","https://openalex.org/W1686810756","https://openalex.org/W1988189469","https://openalex.org/W2015268891","https://openalex.org/W2023302299","https://openalex.org/W2046217261","https://openalex.org/W2054780155","https://openalex.org/W2097847401","https://openalex.org/W2102372511","https://openalex.org/W2157770256","https://openalex.org/W2183341477","https://openalex.org/W2242223225","https://openalex.org/W2249376573","https://openalex.org/W2288074780","https://openalex.org/W2355170876","https://openalex.org/W2552002155","https://openalex.org/W2736191430","https://openalex.org/W2770967835","https://openalex.org/W2785511981","https://openalex.org/W2789436454","https://openalex.org/W2898693178","https://openalex.org/W2953001150","https://openalex.org/W2954377489","https://openalex.org/W2964137095","https://openalex.org/W6637373629","https://openalex.org/W6662113552","https://openalex.org/W6674941753","https://openalex.org/W6696429117","https://openalex.org/W6705739769"],"related_works":["https://openalex.org/W2120540196","https://openalex.org/W3095343173","https://openalex.org/W2381036744","https://openalex.org/W2288135719","https://openalex.org/W2323749021","https://openalex.org/W2533590149","https://openalex.org/W2901989338","https://openalex.org/W82005754","https://openalex.org/W2334448276","https://openalex.org/W3210733254"],"abstract_inverted_index":{"Many":[0],"deep":[1],"learning":[2],"(DL)":[3],"models":[4],"have":[5],"shown":[6],"exceptional":[7],"promise":[8],"in":[9,61],"radar-based":[10,17],"human":[11],"activity":[12],"recognition":[13,85,145],"(HAR)":[14],"area.":[15],"For":[16],"HAR,":[18],"the":[19,36,41,49,91,94,129,137,143,153],"raw":[20],"data":[21,139],"is":[22,97],"generally":[23],"converted":[24],"into":[25],"a":[26,74,78,100,109],"2-D":[27,54,65],"spectrogram":[28,42,96],"by":[29],"using":[30],"short-time":[31],"Fourier":[32],"transform":[33],"(STFT).":[34],"All":[35],"existing":[37,154],"DL":[38,110],"methods":[39,66],"treat":[40],"as":[43,53,99],"an":[44],"optical":[45],"image,":[46],"and":[47,119,140,147],"thus":[48,141],"corresponding":[50],"architectures":[51],"such":[52],"convolutional":[55,115],"neural":[56,116],"networks":[57,117],"(2D-CNNs)":[58],"are":[59],"adopted":[60],"those":[62],"methods.":[63,156],"These":[64],"that":[67,128],"ignore":[68],"temporal":[69],"characteristics":[70,135],"ordinarily":[71],"lead":[72],"to":[73,152],"complex":[75],"network":[76],"with":[77,103],"huge":[79],"amount":[80],"of":[81,113,136],"parameters":[82],"but":[83],"limited":[84],"accuracy.":[86],"In":[87],"this":[88],"paper,":[89],"for":[90],"first":[92],"time,":[93],"radar":[95,138],"treated":[98],"time":[101],"sequence":[102],"multiple":[104],"channels.":[105],"Hence,":[106],"we":[107],"propose":[108],"model":[111,131],"composed":[112],"1-D":[114],"(1D-CNNs)":[118],"long":[120],"short-term":[121],"memory":[122],"(LSTM).":[123],"The":[124],"experiments":[125],"results":[126],"show":[127],"proposed":[130],"can":[132],"extract":[133],"spatio-temporal":[134],"achieves":[142],"best":[144],"accuracy":[146],"relatively":[148],"low":[149],"complexity":[150],"compared":[151],"2D-CNN":[155]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":29},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2020-02-14T00:00:00"}
