Automatic Fall Detection using Deep Neural Networks with Aggregated Residual Transformation-Reference-Cited by-同舟云学术

Automatic Fall Detection using Deep Neural Networks with Aggregated Residual Transformation

Published:2022-07-05 Issue: Volume: Page:
ISSN:
Container-title:2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC)
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Author:

Mekruksavanich Sakorn¹,Jantawong Ponnipa¹,Hnoohom Narit²,Jitpattanakul Anuchit³

Affiliation:

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

2. Mahidol University,Image, Information and Intelligence Laboratory, Faculty of Engineering,Department of Computer Engineering,Nakhon Pathom,Thailand

3. 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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9894733/9894851/09895054.pdf?arnumber=9895054

Reference20 articles.

1. Deep Learning Approaches for Continuous Authentication Based on Activity Patterns Using Mobile Sensing

2. Human fall detection with smartphones

3. Fall Detection from Smart Wearable Sensors using Deep Convolutional Neural Network with Squeeze-and-Excitation Module

4. Deep Residual Network for Smartwatch-Based User Identification through Complex Hand Movements

5. A Hybrid Deep Residual Network for Efficient Transitional Activity Recognition Based on Wearable Sensors

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