Search Results for author:
Found 4 papers, 0 papers with code
Through-life Monitoring of Resource-constrained Systems and Fleets
A Digital Twin (DT) is a simulation of a physical system that provides information to make decisions that add economic, social or commercial value.
In-flight Novelty Detection with Convolutional Neural Networks
This paper proposes that system output measurements, described by a convolutional neural network model of normality, are prioritised in real-time for the attention of preventative maintenance decision makers.
A temporal-to-spatial deep convolutional neural network for classification of hand movements from multichannel electromyography data
The temporal layer captures these signature features for each channel separately, which are then spatially mixed in successive layers to recognise a specific gesture.
Compact Deep Neural Networks for Computationally Efficient Gesture Classification From Electromyography Signals
The accuracy of the compact deep net was found to be 84. 2 +/- 6% versus 70. 5 +/- 7% for the SVM on the Myo, and 80. 3+/- 7% versus 67. 8 +/- 9% for the Delsys system, demonstrating the superior effectiveness of the proposed compact network, which had just 5, 889 parameters - orders of magnitude less than some contemporary alternatives in this domain while maintaining better performance.
