4 citations · 8 across the 6 of their papers we have counts for
6 papers
Active transfer learning for structural health monitoring
J. Poole, N. Dervilis, K. Worden +4
Data for training structural health monitoring (SHM) systems are often expensive and/or impractical to obtain, particularly for labelled data. Population-based SHM (PBSHM) aims to…
Physics-informed transfer learning for SHM via feature selection
J. Poole, P. Gardner, A. J. Hughes +4
Data used for training structural health monitoring (SHM) systems are expensive and often impractical to obtain, particularly labelled data. Population-based SHM presents a potenti…
Quantifying the value of positive transfer: An experimental case study
Aidan J. Hughes, Giulia Delo, Jack Poole +2
In traditional approaches to structural health monitoring, challenges often arise associated with the availability of labelled data. Population-based structural health monitoring s…
Quantifying the value of information transfer in population-based SHM
Aidan J. Hughes, Jack Poole, Nikolaos Dervilis +2
Population-based structural health monitoring (PBSHM), seeks to address some of the limitations associated with data scarcity that arise in traditional SHM. A tenet of the populati…
A decision framework for selecting information-transfer strategies in population-based SHM
Aidan J. Hughes, Jack Poole, Nikolaos Dervilis +2
Decision-support for the operation and maintenance of structures provides significant motivation for the development and implementation of structural health monitoring (SHM) system…
On statistic alignment for domain adaptation in structural health monitoring
Jack Poole, Paul Gardner, Nikolaos Dervilis +2
The practical application of structural health monitoring (SHM) is often limited by the availability of labelled data. Transfer learning - specifically in the form of domain adapta…