Identification of Gait Patterns using Convolutional Neural Networks for Personal Authentication
Author:
Funder
Gangneung-Wonju National University
Ministry of Education
National Research Foundation of Korea
Publisher
Korean Institute of Information Technology
Reference24 articles.
1. Y. Kim, "Fourth Industrial Revolution(4IR) Hyper-Connected Society and Internet of Things Age", Journal of the Korean Contents Association, Vol. 17, No. 3, pp. 14-19, 2019.
2. Accelerometer-Based Speed-Adaptive Gait Authentication Method for Wearable IoT Devices
3. Continuous authentication of smartphone users based on activity pattern recognition using passive mobile sensing
4. IDNet: Smartphone-based gait recognition with convolutional neural networks
5. KEH-Gait: Using Kinetic Energy Harvesting for Gait-based User Authentication Systems
Cited by 3 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. Robust Personal Identification Using Wearable Devices Based on LSTM and CNN;Journal of Sensors;2023-07-18
2. Personal Identification CNN Model using Gait Cycle;The Journal of Korean Institute of Information Technology;2022-11-30
3. Smartphone Authentication System using Personal Gaits and CNN;The Journal of Korean Institute of Information Technology;2022-10-31
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