Deep Learning for Human Activity Recognition Based on Causality Feature Extraction

Deep Learning for Human Activity Recognition Based on Causality Feature Extraction

We propose a novel data-driven feature extraction approach based on direct causality and fuzzy temporal windows (FTWs) to improve the precision of human activity recognition and mitigate the problems of easily-confused activities and unlabeled data, which significantly degrade classification perform...

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Bibliographic Details
Main Authors: Yu Min Hwang, Sangjun Park, Hyung Ok Lee, Seok-Kap Ko, Byung-Tak Lee
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Activity of daily living
activity recognition
causality
convolutional neural network
deep learning
fuzzy feature
Online Access:https://ieeexplore.ieee.org/document/9509017/

Internet

https://ieeexplore.ieee.org/document/9509017/

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