Motion learning using spatio-temporal neural network
Motion trajectory prediction is one of the key areas in behaviour and surveillance studies. Many related successful applications have been reported in the literature. However, most of the studies are based on sigmoidal neural networks in which some dynamic properties of the data are overlooked due...
Main Authors: | Yusoff, Nooraini, Ahmad, Farzana Kabir, Jemili, Mohamad Farif |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Utara Malaysia
2020
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/26942/1/JICT%2019%202%202020%20%20207-223.pdf |
Similar Items
-
Learning stimulus-stimulus association in spatio-temporal neural networks
by: Yusoff, Nooraini, et al.
Published: (2015) -
Learning anticipation through priming in spatio-temporal neural networks
by: Yusoff, Nooraini, et al.
Published: (2012) -
Stimulus-stimulus association via reinforcement learning in spiking neural network
by: Yusoff, Nooraini, et al.
Published: (2013) -
Biologically inspired temporal sequence learning
by: Yusoff, Nooraini, et al.
Published: (2012) -
Supervised associative learning in spiking neural network
by: Yusoff, Nooraini, et al.
Published: (2010)