A Comparative Study of Deep Learning Robustness for Sensor-based Human Activity Recognition-Reference-Cited by-同舟云学术

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A Comparative Study of Deep Learning Robustness for Sensor-based Human Activity Recognition

Published:2023-07-12 Issue: Volume: Page:
ISSN:
Container-title:2023 46th International Conference on Telecommunications and Signal Processing (TSP)
language:
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Author:

Mekruksavanich Sakorn¹,Jitpattanakul Anuchit²

Affiliation:

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

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

Funder

Thailand Science Research and Innovation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10197649/10197641/10197695.pdf?arnumber=10197695

Reference22 articles.

1. A Comparative Research on Human Activity Recognition Using Deep Learning

2. Describing the User Experience of Wearable Fitness Technology through Online Product Reviews

3. Recognition of Real-life Activities with Smartphone Sensors using Deep Learning Approaches

4. Deep learning for sensor-based activity recognition: A survey

5. A Deep Bidirectional GRU Network Model for Biometric Electrocardiogram Classification Based on Recurrent Neural Networks

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. Sensor-Based Analysis of Manual Processes in Production and Logistics: Motion-Mining versus Lean Tools;Lecture Notes in Logistics;2024

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