Dynamic Gesture Recognition Model Based on Millimeter-Wave Radar With ResNet-18 and LSTM

Dynamic Gesture Recognition Model Based on Millimeter-Wave Radar With ResNet-18 and LSTM

In this article, a multi-layer convolutional neural network (ResNet-18) and Long Short-Term Memory Networks (LSTM) model is proposed for dynamic gesture recognition. The Soli dataset is based on the dynamic gesture signals collected by millimeter-wave radar. As a gesture sensor radar, Soli radar has...

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Bibliographic Details
Main Authors:	Liu, S. (Author), Ma, G. (Author), Man, M. (Author), Peng, L. (Author), Zhang, Y. (Author)
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2022
Subjects:	article Convolutional neural network explosion gesture gesture recognition Gesture recognition Gestures recognition human human computer interaction Human computer interaction Human-Computer Interaction long short term memory network Long short-term memory Long short-term memory network LSTM Memory network Millimeter waves millimeter-wave radar Millimeter-wave radar Millimetre-wave radar Model-based OPC Multilayer neural networks Multi-layers Network layers Radar Recognition models residual neural network Resnet-18 ResNet-18 telecommunication validity
Online Access:	View Fulltext in Publisher

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