All Outputs (7)

A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers (2020)
Conference Proceeding

Transhumeral amputation has a considerable detrimental effect on the amputee’s quality of life and independence. Previous work has already established the potential for exploiting proximal humerus myoelectric and kinematic signals for the effective c... Read More about A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers.

Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images (2019)
Conference Proceeding

Edge detection in Musculoskeletal Ultrasound Imaging readily allows an ultrasound image to be rendered as a binary image. This facilitates automated measurement of geometric parameters, such as muscle thickness, circumference and cross-sectional area... Read More about Using Fuzzy Inference system for detection the edges of Musculoskeletal Ultrasound Images.

Enhancement of Panoramic Musculoskeletal Ultrasound Image Based on Fuzzy Technique (2019)
Conference Proceeding

Panoramic Musculoskeletal Ultrasound Images (PMUI) is a developed version of ultrasound images. However, low contrast is a concrete problem which impact negatively on the interpretation of important details of PMUI. Therefore, in this paper a new aut... Read More about Enhancement of Panoramic Musculoskeletal Ultrasound Image Based on Fuzzy Technique.

Fault Detection in Steel-Reinforced Concrete Using Echo State Networks (2018)
Conference Proceeding

The cost of maintaining and repairing the world's ageing reinforced concrete infrastructure continues to increase, and is expected to cost the United States economy alone $58 billion by 2020. Consequently, the use of non-destructive testing technolog... Read More about Fault Detection in Steel-Reinforced Concrete Using Echo State Networks.

Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer (2017)
Conference Proceeding

Lung cancer is a widespread disease and it is well understood that systematic, non-invasive and early detection of this progressive and life-threatening disorder is of vital importance for patient outcomes. In this work we present a convergence of fa... Read More about Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer.

Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images (2016)
Conference Proceeding

Fast and accurate segmentation of musculoskeletal ultrasound images is an on-going challenge. Two principal factors make this task difficult: firstly, the presence of speckle noise arising from the interference that accompanies all coherent imaging a... Read More about Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images.

An Echo State Network Approach to Structural Health Monitoring (2015)
Conference Proceeding

Echo State Networks (ESNs) have been applied to time-series data arising from a structural health monitoring multi-sensor array placed onto a test footbridge which has been subjected to a number of potentially damaging interventions over a three year... Read More about An Echo State Network Approach to Structural Health Monitoring.