{"id":"https://openalex.org/W2789436454","doi":"https://doi.org/10.1109/taes.2018.2799758","title":"Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities","display_name":"Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities","publication_year":2018,"publication_date":"2018-02-06","ids":{"openalex":"https://openalex.org/W2789436454","doi":"https://doi.org/10.1109/taes.2018.2799758","mag":"2789436454"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2018.2799758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2018.2799758","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-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/A5077343004","display_name":"Mehmet Sayg\u0131n Seyfio\u011flu","orcid":null},"institutions":[{"id":"https://openalex.org/I13236232","display_name":"TOBB University of Economics and Technology","ror":"https://ror.org/03ewx7v96","country_code":"TR","type":"education","lineage":["https://openalex.org/I13236232"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Mehmet Saygin Seyfioglu","raw_affiliation_strings":["TOBB University of Economics and Technology, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TOBB University of Economics and Technology, Ankara, Turkey","institution_ids":["https://openalex.org/I13236232"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048947308","display_name":"Ahmet Murat \u00d6zbayo\u011flu","orcid":"https://orcid.org/0000-0001-7998-5735"},"institutions":[{"id":"https://openalex.org/I13236232","display_name":"TOBB University of Economics and Technology","ror":"https://ror.org/03ewx7v96","country_code":"TR","type":"education","lineage":["https://openalex.org/I13236232"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ahmet Murat Ozbayoglu","raw_affiliation_strings":["TOBB University of Economics and Technology, Ankara, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TOBB University of Economics and Technology, Ankara, Turkey","institution_ids":["https://openalex.org/I13236232"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025392795","display_name":"Sevgi Z\u00fcbeyde G\u00fcrb\u00fcz","orcid":"https://orcid.org/0000-0001-7487-9087"},"institutions":[{"id":"https://openalex.org/I17301866","display_name":"University of Alabama","ror":"https://ror.org/03xrrjk67","country_code":"US","type":"education","lineage":["https://openalex.org/I17301866"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sevgi Zubeyde Gurbuz","raw_affiliation_strings":["University of Alabama, Tuscaloosa, AL, USA"],"raw_orcid":"https://orcid.org/0000-0001-7487-9087","affiliations":[{"raw_affiliation_string":"University of Alabama, Tuscaloosa, AL, USA","institution_ids":["https://openalex.org/I17301866"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":393.442,"has_fulltext":false,"cited_by_count":359,"citation_normalized_percentile":{"value":0.99992911,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"54","issue":"4","first_page":"1709","last_page":"1723"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9997000098228455,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9983000159263611,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9927999973297119,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9388293027877808},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.770942747592926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7506569623947144},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6891462802886963},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6837453842163086},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6649532318115234},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6436939835548401},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6303380727767944},{"id":"https://openalex.org/keywords/doppler-radar","display_name":"Doppler radar","score":0.5581969022750854},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.45391279458999634},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4335816204547882},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08521768450737}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9388293027877808},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.770942747592926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7506569623947144},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6891462802886963},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6837453842163086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6649532318115234},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6436939835548401},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6303380727767944},{"id":"https://openalex.org/C2778559676","wikidata":"https://www.wikidata.org/wiki/Q1334213","display_name":"Doppler radar","level":3,"score":0.5581969022750854},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.45391279458999634},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4335816204547882},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08521768450737}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2018.2799758","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2018.2799758","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1495619764","https://openalex.org/W1522301498","https://openalex.org/W1533539416","https://openalex.org/W1560002189","https://openalex.org/W1665214252","https://openalex.org/W1686810756","https://openalex.org/W1989797986","https://openalex.org/W2022102190","https://openalex.org/W2043415540","https://openalex.org/W2045423428","https://openalex.org/W2047129912","https://openalex.org/W2055590061","https://openalex.org/W2078409967","https://openalex.org/W2082302382","https://openalex.org/W2082361295","https://openalex.org/W2094602257","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2114354118","https://openalex.org/W2114394209","https://openalex.org/W2119387367","https://openalex.org/W2136655611","https://openalex.org/W2138857742","https://openalex.org/W2140578616","https://openalex.org/W2141200610","https://openalex.org/W2148143831","https://openalex.org/W2154579312","https://openalex.org/W2157770256","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2194775991","https://openalex.org/W2242223225","https://openalex.org/W2249376573","https://openalex.org/W2271840356","https://openalex.org/W2295598076","https://openalex.org/W2298692413","https://openalex.org/W2329339966","https://openalex.org/W2350054051","https://openalex.org/W2437887222","https://openalex.org/W2501169257","https://openalex.org/W2507582775","https://openalex.org/W2515467440","https://openalex.org/W2531174837","https://openalex.org/W2563851357","https://openalex.org/W2577021971","https://openalex.org/W2618530766","https://openalex.org/W2625773758","https://openalex.org/W2964121744","https://openalex.org/W3102476541","https://openalex.org/W4394650427","https://openalex.org/W6629590435","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6674330103","https://openalex.org/W6676889274","https://openalex.org/W6679997575","https://openalex.org/W6680300913","https://openalex.org/W6680949248","https://openalex.org/W6682751323","https://openalex.org/W6694517276","https://openalex.org/W6696356757","https://openalex.org/W6725218734","https://openalex.org/W6731853769"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W4372048956","https://openalex.org/W4206989953","https://openalex.org/W4283776244"],"abstract_inverted_index":{"Radar-based":[0],"activity":[1],"recognition":[2],"is":[3,59,76],"a":[4,53,124,141],"problem":[5],"that":[6],"has":[7],"been":[8],"of":[9,37,118,128,133],"great":[10],"interest":[11],"due":[12],"to":[13,33,40,65,78],"applications":[14],"such":[15,87,102],"as":[16,88,94,96,103],"border":[17],"control":[18],"and":[19,26,92,110],"security,":[20],"pedestrian":[21],"identification":[22],"for":[23,130],"automotive":[24],"safety,":[25],"remote":[27],"health":[28],"monitoring.":[29],"This":[30,74],"paper":[31],"seeks":[32],"show":[34,115],"the":[35,67,70,116,119],"efficacy":[36],"micro-Doppler":[38,46,131],"analysis":[39],"distinguish":[41],"even":[42],"those":[43],"gaits":[44],"whose":[45],"signatures":[47,132],"are":[48],"not":[49],"visually":[50],"distinguishable.":[51],"Moreover,":[52],"three-layer,":[54],"deep":[55,84,121],"convolutional":[56,72,89],"autoencoder":[57],"(CAE)":[58],"proposed,":[60],"which":[61],"utilizes":[62],"unsupervised":[63],"pretraining":[64],"initialize":[66],"weights":[68],"in":[69],"subsequent":[71],"layers.":[73],"architecture":[75],"shown":[77],"be":[79],"more":[80],"effective":[81],"than":[82],"other":[83],"learning":[85],"architectures,":[86],"neural":[90],"networks":[91],"autoencoders,":[93],"well":[95],"conventional":[97],"classifiers":[98],"employing":[99],"predefined":[100],"features,":[101],"support":[104],"vector":[105],"machines":[106],"(SVM),":[107],"random":[108],"forest,":[109],"extreme":[111],"gradient":[112],"boosting.":[113],"Results":[114],"performance":[117],"proposed":[120],"CAE":[122],"yields":[123],"correct":[125],"classification":[126],"rate":[127],"94.2%":[129],"12":[134],"different":[135],"human":[136],"activities":[137],"measured":[138],"indoors":[139],"using":[140],"4":[142],"GHz":[143],"continuous":[144],"wave":[145],"radar-17.3%":[146],"improvement":[147],"over":[148],"SVM.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":32},{"year":2024,"cited_by_count":41},{"year":2023,"cited_by_count":44},{"year":2022,"cited_by_count":46},{"year":2021,"cited_by_count":79},{"year":2020,"cited_by_count":53},{"year":2019,"cited_by_count":44},{"year":2018,"cited_by_count":15}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}