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Smartphone Based Human Activity Recognition Using 1D Lightweight Convolutional Neural Network

  • Published:2022-02-06 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 International Conference on Electronics, Information, and Communication (ICEIC)
  • language:
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Author:

Yi Myung-Kyu1,Hwang Seong Oun1

Affiliation:

1. Gachon University,Department of Computer Engineering,Republic of Korea

Funder

MSIT (Ministry of Science, ICT), Korea

IITP (Institute for Information & Communications Technology Planning & Evaluation)

National Research Foundation of Korea (NRF)

Publisher

IEEE

Cited by 5 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. Genetic Algorithm Optimized BiLSTM Networks Model for Human Activity Recognition using Timeseries Sensor Data;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11

2. A lightweight fast human activity recognition method using hybrid unsupervised-supervised feature;Neural Computing and Applications;2023-03-02

3. Novel Deep Learning Network for Gait Recognition Using Multimodal Inertial Sensors;Sensors;2023-01-11

4. On-Device Personalization for Human Activity Recognition on STM32;IEEE Embedded Systems Letters;2023

5. A Neural Network Pruning Approach to Human Activity Identification Based on Deep Learning;2022 IEEE International Conference on Current Development in Engineering and Technology (CCET);2022-12-23
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