Triple Parallel LSTM Networks for Classifying the Gait Disorders Using Kinect Camera and Robot Platform During the Clinical Examination-Reference-Cited by-同舟云学术

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Triple Parallel LSTM Networks for Classifying the Gait Disorders Using Kinect Camera and Robot Platform During the Clinical Examination

Published:2023-07-19 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
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Author:

Shayestegan Mohsen¹,Zalabsky Tomas²,Mareš Jan³

Affiliation:

1. University of Pardubice Pardubice,Faculty of Electrical Engineering and Informatics,Czech Republic

2. Research Center University of Pardubice Pardubice,Faculty of Electrical Engineering and Informatics,Czech Republic

3. University of Pardubice Pardubice,Faculty of Electrical Engineering and Informatics,Department of Process Control,Czech Republic

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10252163/10252090/10252459.pdf?arnumber=10252459

Reference24 articles.

1. A Spatiotemporal Deep Learning Approach for Automatic Pathological Gait Classification

2. Pytorch: An imperative style, high-performance deep learning library;paszke;Advances in neural information processing systems,2019

3. Pathological Gait Detection Based on Multiple Regression Models Using Unobtrusive Sensing Technology

4. Power Transformer Operating State Prediction Method Based on an LSTM Network

5. Stacked bidirectional and unidirectional LSTM recurrent neural network for forecasting network-wide traffic state with missing values

Cited by 1 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. Skeleton-Based Gait Recognition Using Modified Deep Convolutional Neural Networks and Long Short-Term Memory for Person Recognition;IEEE Access;2024

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