Attention Based Hybrid Deep Learning Network for Locomotive Mode Recognition in Natural Environments Using Wearable Sensors-Reference-Cited by-同舟云学术

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Attention Based Hybrid Deep Learning Network for Locomotive Mode Recognition in Natural Environments Using Wearable Sensors

Published:2023-08-24 Issue: Volume: Page:
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Container-title:2023 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)
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Author:

Mekruksavanich Sakorn¹,Jantawong Ponnipa¹,Jitpattanakul Anuchit²

Affiliation:

1. School of Information and Communication Technology, University of Phayao,Department of Computer Engineering,Phayao,Thailand

2. King Mongkut's University of Technology North Bangkok,Intelligent and Nonlinear Dynamic Innovations Research Center, Faculty of Applied Science,Department of Mathematics,Bangkok,Thailand

Funder

University of Phayao

King Mongkut's University of Technology North Bangkok

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10355960/10355935/10356026.pdf?arnumber=10356026

Reference26 articles.

1. Recognition of human locomotion on various transportations fusing smartphone sensors

2. FallNeXt: A Deep Residual Model based on Multi-Branch Aggregation for Sensor-based Fall Detection

3. Real-Time Hybrid Locomotion Mode Recognition for Lower Limb Wearable Robots

4. Classification of Gait Pattern with Wearable Sensing Data

5. Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review

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