RF-Based Human Activity Recognition Using Signal Adapted Convolutional Neural Network-Reference-Cited by-同舟云学术

RF-Based Human Activity Recognition Using Signal Adapted Convolutional Neural Network

Published:2021 Issue: Volume: Page:1-1
ISSN:1536-1233
Container-title:IEEE Transactions on Mobile Computing
language:
Short-container-title:IEEE Trans. on Mobile Comput.

Author:

Chen Zhe¹,Cai Chao²,Zheng Tianyue³,Luo Jun⁴,Xiong Jie⁵,Wang Xin⁶

Affiliation:

1. School of Computer Science and Engineering, Nanyang Technological University, 54761 Singapore, Singapore, Singapore, (e-mail: nick.chitchan@gmail.com)

2. School of Computer Science and Engineering, Nanyang Technological University, 54761 Singapore, Singapore, Singapore, 639798 (e-mail: chris.cai@ntu.edu.sg)

3. School of Computer Science and Engineering, Nanyang Technological University, 54761 Singapore, Singapore, Singapore, (e-mail: tianyue002@e.ntu.edu.sg)

4. School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore, Singapore, 639798 (e-mail: junluo@ntu.edu.sg)

5. College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, Massachusetts, United States, (e-mail: jxiong@cs.umass.edu)

6. School of Computer Science, Fudan University, Shanghai, ShangHai, China, (e-mail: xinw@fudan.edu.cn)

Funder

MoE Tier 1 Singapore

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Software

Link

http://xplorestaging.ieee.org/ielx7/7755/4358975/09408395.pdf?arnumber=9408395

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