All Outputs (4)

Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species (2017)
Journal Article

Blowflies (Diptera: Calliphoridae) are forensically important as they are known to be one of the first to colonise human remains. The larval stage is typically used to assist a forensic entomologists with adult flies rarely used as they are difficult... Read More about Adult fly age estimations using cuticular hydrocarbons and Artificial Neural Networks in forensically important Calliphoridae species.

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.

Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX (2017)
Journal Article

Echo State Networks (ESNs) and a Nonlinear Auto-Regressive Moving Average model with eXogenous inputs (NARMAX) have been applied to multi-sensor time-series data arising from a test footbridge which has been subjected to multiple potentially damaging... Read More about Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX.

Optimizing Echo State Networks for Static Pattern Recognition (2017)
Journal Article

Static pattern recognition requires a machine to classify an object on the basis of a combination of attributes and is typically performed using machine learning techniques such as support vector machines and multilayer perceptrons. Unusually, in thi... Read More about Optimizing Echo State Networks for Static Pattern Recognition.