Philip Boreham

According to our database, Philip Boreham authored at least 16 papers between 2017 and 2022.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2022

Dynamic Noise Reduction with Deep Residual Shrinkage Networks for Online Fault Classification.

Alireza Salimy, Imene Mitiche, Philip Boreham, Alan Nesbitt, Gordon Morison

Sensors, 2022

Can a deep learning based IoT fault diagnosis system identify more than one fault at a time?

Alireza Salimy, Imene Mitiche, Philip Boreham, Alan Nesbitt, Gordon Morison

Proceedings of the IEEE International Conference on Internet of Things and Intelligence Systems, 2022

Unsupervised Source Separation for Multi-Label Classification.

Imene Mitiche, Alireza Salimy, Philip Boreham, Tony McGrail, Alan Nesbitt, Gordon Morison

Proceedings of the 30th European Signal Processing Conference, 2022

2021

Data-Driven Anomaly Detection in High-Voltage Transformer Bushings with LSTM Auto-Encoder.

Imene Mitiche, Tony McGrail, Philip Boreham, Alan Nesbitt, Gordon Morison

Sensors, 2021

An expert system for EMI data classification based on complex Bispectrum representation and deep learning methods.

Imene Mitiche, Mark David Jenkins, Philip Boreham, Alan Nesbitt, Gordon Morison

Expert Syst. Appl., 2021

Robust Deep Residual Shrinkage Networks for Online Fault Classification.

Alireza Salimy, Imene Mitiche, Philip Boreham, Alan Nesbitt, Gordon Morison

Proceedings of the 29th European Signal Processing Conference, 2021

OODCN: Out-Of-Distribution Detection in Capsule Networks for Fault Identification.

Imene Mitiche, Alireza Salimy, Falk Werner, Philip Boreham, Alan Nesbitt, Gordon Morison

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Low Complexity Classification of Power Asset Faults for Real Time IoT-based Diagnostics.

Alireza Salimy, Imene Mitiche, Philip Boreham, Alan Nesbitt, Gordon Morison

Proceedings of the IEEE Global Conference on Artificial Intelligence and Internet of Things, 2020

2019

Deep Complex Neural Network Learning for High-Voltage Insulation Fault Classification from Complex Bispectrum Representation.

Imene Mitiche, Mark David Jenkins, Philip Boreham, Alan Nesbitt, Gordon Morison

Proceedings of the 27th European Signal Processing Conference, 2019

A Hybrid Cloud for Data Analytics in Electrical Substation Condition Monitoring Systems.

Jack Slater, Alan Nesbitt, Gordon Morison, Philip Boreham

Proceedings of the 2019 IEEE International Conference on Computational Science and Engineering, 2019

2018

Imaging Time Series for the Classification of EMI Discharge Sources.

Imene Mitiche, Gordon Morison, Alan Nesbitt, Michael Hughes-Narborough, Brian G. Stewart, Philip Boreham

Sensors, 2018

Classification of Partial Discharge Signals by Combining Adaptive Local Iterative Filtering and Entropy Features.

Imene Mitiche, Gordon Morison, Alan Nesbitt, Michael Hughes-Narborough, Brian G. Stewart, Philip Boreham

Sensors, 2018

Entropy-Based Feature Extraction for Electromagnetic Discharges Classification in High-Voltage Power Generation.

Imene Mitiche, Gordon Morison, Alan Nesbitt, Brian G. Stewart, Philip Boreham

Entropy, 2018

Naive Bayes Multi-Label Classification Approach for High-Voltage Condition Monitoring.

Imene Mitiche, Alan Nesbitt, Philip Boreham, Brian G. Stewart, Gordon Morison

Proceedings of the IEEE International Conference on Internet of Things and Intelligence System, 2018

Deep Residual Neural Network for EMI Event Classification Using Bispectrum Representations.

Imene Mitiche, Mark David Jenkins, Philip Boreham, Alan Nesbitt, Brian G. Stewart, Gordon Morison

Proceedings of the 26th European Signal Processing Conference, 2018

2017

Classification of partial discharge EMI conditions using permutation entropy-based features.

Imene Mitiche, Gordon Morison, Alan Nesbitt, Philip Boreham, Brian G. Stewart

Proceedings of the 25th European Signal Processing Conference, 2017