Self-organizing reservoir network for action recognition
Current research in human action recognition (HAR) focuses on efficient and effective modelling of the temporal features of human actions in 3-dimensional space. Echo State Networks (ESNs) are one suitable method for encoding the temporal context due to its short-term memory property. However, the r...
Saved in:
Main Authors: | Lee, Gin Chong, Loo, Chu Kiong, Liew, Wei Shiung |
---|---|
Format: | Article |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/41787/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
On the post hoc explainability of optimized self-organizing reservoir network for action recognition
by: Lee, Gin Chong, et al.
Published: (2022) -
Self-organizing kernel-based convolutional echo state network for human action recognition / Lee Gin Chong
by: Lee , Gin Chong
Published: (2022) -
Reservoir computing with truncated normal distribution for speech emotion recognition
by: Ibrahim, Hemin, et al.
Published: (2022) -
A dual fast and slow feature interaction in biologically inspired visual recognition of human action
by: Yousefi, Bardia, et al.
Published: (2018) -
Bidirectional parallel echo state network for speech emotion recognition
by: Ibrahim, Hemin, et al.
Published: (2022)