Comparison of Deep Learning Techniques on Human Activity Recognition using Ankle Inertial Signals

Author:

Nazari Farhad1,Nahavandi Darius1,Mohajer Navid1,Khosravi Abbas1

Affiliation:

1. Deakin University,Institute for Intelligent System Research and Innovation (IISRI),Australia

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimum signal duration for Human Activity Recognition based on Deep Convolutional Neural Networks;2024 IEEE International Systems Conference (SysCon);2024-04-15

2. Real-Time Sensor-Embedded Neural Network for Human Activity Recognition;Sensors;2023-09-28

3. Classification of gait phases based on a machine learning approach using muscle synergy;Frontiers in Human Neuroscience;2023-05-17

4. Comparison of gait phase detection using traditional machine learning and deep learning techniques;2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2022-10-09

5. A Prediction of Time Series Driving Motion Scenarios Using LSTM and ESN;2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2022-10-09

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