Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities

Radar-based activity recognition is a problem that has been of great interest due to applications such as border control and security, pedestrian identification for automotive safety, and remote health monitoring. This paper seeks to show the efficacy of micro-Doppler analysis to distinguish even th...

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Vydané v:	IEEE transactions on aerospace and electronic systems Ročník 54; číslo 4; s. 1709 - 1723
Hlavní autori:	Seyfioglu, Mehmet Saygin, Ozbayoglu, Ahmet Murat, Gurbuz, Sevgi Zubeyde
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Activity recognition Artificial neural networks Assisted living Classification Continuous wave radar Convolutional autoencoder (CAE) deep learning Diagnostic systems Feature recognition gait recognition Legged locomotion Machine learning micro-Doppler Neural networks Pedestrian safety Radar Radar signatures Remote monitoring Spectrogram Support vector machines
ISSN:	0018-9251, 1557-9603
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