Jul 27, 2022 · The aim of this paper is to propose a lightweight and accurate recurrent neural network (RNN) that can be implemented on a low cost, low power core.
The aim of this paper is to address the HAR task directly on a wearable device, implementing a recurrent neural network (RNN) on a low cost, low power ...
A Lightweight and Accurate RNN in Wearable Embedded Systems for Human Activity Recognition. L. Falaschetti, G. Biagetti, P. Crippa, M. Alessandrini, ...
The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low ...
Mar 3, 2024 · Human Activity Recognition (HAR) is the automatic detection and understanding of human motion behavior based on data extracted from video ...
The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low ...
The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low ...
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Jun 2, 2021 · CNN-LSTM, a proposed model, is an efficient and lightweight model that has shown high robustness and better activity detection capability than traditional ...
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The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low ...
May 1, 2024 · In this work, we propose a lightweight, deep learning-based, multiperson activity recognition system for group exercise training of elderly persons.