The effect of network depth in neural network for human gait cycle prediction
Artificial neural networks were implemented satisfactorily to assess gait events from various walking data. This research is to study the suitable network depth in neural network technique for developing human gait cycle prediction model using artificial neural network. Gait dataset is retrieved fro...
Published in: | AIP Conference Proceedings |
---|---|
Main Author: | 2-s2.0-85166760836 |
Format: | Conference paper |
Language: | English |
Published: |
American Institute of Physics Inc.
2023
|
Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166760836&doi=10.1063%2f5.0117708&partnerID=40&md5=184a297c9ec3bb6eea26c2f3d7094c0d |
Similar Items
-
Systematic Literature Review: Recognition of Human Gait Cycle Using Machine Learning Approach
by: 2-s2.0-85136505986
Published: (2022) -
Predicting fraudulent financial reporting using artificial neural network
by: 2-s2.0-85019490600
Published: (2017) -
A neural network students' performance prediction model (NNSPPM)
by: 2-s2.0-84894188408
Published: (2013) -
Flood prediction using NARX neural network and EKF prediction technique: A comparative study
by: 2-s2.0-84891096883
Published: (2013) -
Artificial Neural Network-Salp-Swarm Algorithm for Stock Price Prediction
by: Mustaffa Z.; Sulaiman M.H.; Aziz A.A.
Published: (2024)