Accuracy Comparison of CNN, LSTM, and Transformer for Activity Recognition Using IMU and Visual Markers-Reference-Cited by-同舟云学术

Accuracy Comparison of CNN, LSTM, and Transformer for Activity Recognition Using IMU and Visual Markers

Published:2023 Issue: Volume:11 Page:106650-106669
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Trujillo-Guerrero María Fernanda¹^ORCID,Román-Niemes Stadyn²^ORCID,Jaén-Vargas Milagros¹^ORCID,Cadiz Alfonso³,Fonseca Ricardo³^ORCID,Serrano-Olmedo José Javier¹^ORCID

Affiliation:

1. Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid, Madrid, Spain

2. School of Mathematical and Computational Sciences, Yachay Tech University, Imbabura, Urcuquí, Ecuador

3. Digevo, Santiago, Chile

Funder

Ministerio de Ciencia, Innovación y Universidades of Spain

Cloud Computing

Microsoft Founders Hub

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10261772.pdf?arnumber=10261772

Reference53 articles.

1. Vision Based Human Activity Recognition: A Review

2. Wearable sensors/systems and their impact on biomedical engineering

3. Accelerometry-Based Gait Analysis and Its Application to Parkinson's Disease Assessment— Part 2 : A New Measure for Quantifying Walking Behavior

4. Where to Focus on for Human Action Recognition?

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