C. Chalmers

发表

Simulating Household Electricity Consumption

William Hurst, Mutinta Mwansa, C. Chalmers, 2019 .

A Study into Smart Grid Consumer-User Profiling for Security Applications

William Hurst, Mutinta Mwansa, C. Chalmers, 2018 .

The Categorical Data Conundrum: Heuristics for classification problems – a case study on domestic fire injuries

M. Taylor, P. Fergus, C. Chalmers, 2022, IEEE Access.

Understanding External Influences on Target Detection and Classification Using Camera Trap Images and Machine Learning

S. Longmore, S. Wich, A. Piel, 2022, Sensors.

Noninvasive Technologies for Primate Conservation in the 21st Century

S. Wich, A. Crunchant, A. Piel, 2021, International Journal of Primatology.

An evaluation of platforms for processing camera‐trap data using artificial intelligence

M. A. Tabak, J. Fieberg, W. McShea, 2022, Methods in Ecology and Evolution.

Noninvasive Technologies for Primate Conservation in the 21st Century

S. Wich, A. Crunchant, A. Piel, 2021, International Journal of Primatology.

Recurrent Neural Network Architectures for Analysing Biomedical Data Sets

Dhiya Al-Jumeily, Paul Fergus, Abir Jaafar Hussain, 2017, 2017 10th International Conference on Developments in eSystems Engineering (DeSE).

Remote health monitoring of elderly through wearable sensors

Thar Baker, Muhammad Fahim, Hoshang Kolivand, 2019, Multimedia Tools and Applications.

Empowering Wildlife Guardians: An Equitable Digital Stewardship and Reward System for Biodiversity Conservation using Deep Learning and 3/4G Camera Traps

S. Longmore, S. Wich, E. Meijaard, 2023, Remote. Sens..

The Development of an Arches Resource Model for Recording Radiocarbon Information

Dhiya Al-Jumeily, Abir Jaafar Hussain, Carl Chalmers, 2018, 2018 11th International Conference on Developments in eSystems Engineering (DeSE).

Pressure Ulcer Categorisation using Deep Learning: A Clinical Trial to Evaluate Model Performance

Atif Waraich, W. Henderson, P. Fergus, 2022, ArXiv.

Profiling Users in the Smart Grid

Paul Fergus, William Hurst, Michael Mackay, 2015 .

Smart meter profiling for health applications

Paul Fergus, William Hurst, Michael Mackay, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes pdf

Paul Fergus, Denis Reilly, Carl Chalmers, 2019, IEEE Transactions on Emerging Topics in Computational Intelligence.

Anomaly Detection Using Autoencoder Reconstruction upon Industrial Motors

S. Ortega-Martorell, P. Fergus, C. Chalmers, 2022, Sensors.

Detection of Obstructive Sleep Apnoea Using Features Extracted from Segmented Time-Series ECG Signals Using a One Dimensional Convolutional Neural Network

Paul Fergus, Denis Reilly, Carl Chalmers, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Utilizing Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women

Paul Fergus, Paulo Lisboa, Carl Chalmers, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Remote health monitoring of elderly through wearable sensors

T. Baker, Atif Waraich, H. Kolivand, 2019, Multimedia Tools and Applications.

Robust Interpretation of Genomic Data in Chronic Obstructive Pulmonary Disease (COPD)

Paulo J. G. Lisboa, Dhiya Al-Jumeily, Jade Hind, 2018, 2018 11th International Conference on Developments in eSystems Engineering (DeSE).

Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces

Paul Fergus, Carl Chalmers, Malarvizhi Selvaraj, 2018, Comput. Biol. Medicine.

Utilising Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women

Paul Fergus, Carl Chalmers, Casimiro Aday Curbelo Montañez, 2018 .

Misper-Bayes: A Bayesian Network Model for Missing Person Investigations

Paul Fergus, Mark Taylor, Carl Chalmers, 2021, IEEE Access.

SAERMA: Stacked Autoencoder Rule Mining Algorithm for the Interpretation of Epistatic Interactions in GWAS for Extreme Obesity

C. Aday Curbelo Montañez, Nurul Malim, P. Fergus, 2019, IEEE Access.

A Smart Health Monitoring Technology

Paul Fergus, William Hurst, Michael Mackay, 2016, ICIC.

Modelling Animal Biodiversity Using Acoustic Monitoring and Deep Learning

S. Longmore, S. Wich, P. Fergus, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Extracting Epistatic Interactions in Type 2 Diabetes Genome-Wide Data Using Stacked Autoencoder

P. Fergus, C. Chalmers, B. Abdulaimma, 2018, arXiv.org.

Deep Learning and Genome-Wide Association Studies for the Classification of Type 2 Diabetes

Paul Fergus, Carl Chalmers, Basma Abdulaimma, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Smart Monitoring: An Intelligent System to Facilitate Health Care across an Ageing Population

Paul Fergus, William Hurst, Michael Mackay, 2016 .

Smart Health Monitoring Using the Advance Metering Infrastructure

Paul Fergus, William Hurst, Michael Mackay, 2015, 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing.

An Evaluation of the Factors Affecting ‘Poacher’ Detection with Drones and the Efficacy of Machine-Learning for Detection

S. Longmore, S. Wich, A. Piel, 2021, Sensors.

Choosing an Appropriate Platform and Workflow for Processing Camera Trap Data using Artificial Intelligence

M. A. Tabak, J. Fieberg, P. Fergus, 2022, ArXiv.

BMI: A Behavior Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters pdf

P. Fergus, C. Chalmers, P. Fergus, 2020, ArXiv.

Energy Sobriety: A Behaviour Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters

P. Fergus, C. Chalmers, 2021, Towards Energy Smart Homes.

Machine Learning Techniques for Classification of Livestock Behavior

Dhiya Al-Jumeily, Abir Hussain, Paul Fergus, 2018, ICONIP.

Detecting Activities of Daily Living and Routine Behaviours in Dementia Patients Living Alone Using Smart Meter Load Disaggregation pdf

Paul Fergus, F. Ball, Carl Chalmers, 2019, IEEE Transactions on Emerging Topics in Computing.

Transaction / Regular Paper Title pdf

Paul Fergus, Carl Chalmers, Basma Abdulaimma, 2018 .

Deep Learning Classification of Polygenic Obesity using Genome Wide Association Study SNPs

Dhiya Al-Jumeily, Abir Hussain, Paul Fergus, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces

P. Fergus, C. Chalmers, Malarvizhi Selvaraj, 2018, Comput. Biol. Medicine.

Pressure Ulcer Categorization and Reporting in Domiciliary Settings Using Deep Learning and Mobile Devices: A Clinical Trial to Evaluate End-to-End Performance

Atif Waraich, P. Fergus, C. Chalmers, 2023, IEEE Access.

Collaborative Pressure Ulcer Prevention: An Automated Skin Damage and Pressure Ulcer Assessment Tool for Nursing Professionals, Patients, Family Members and Carers pdf

Paul Fergus, Carl Chalmers, David Tully, 2018, ArXiv.

Identifying behavioural changes for health monitoring applications using the advanced metering infrastructure

Paul Fergus, William Hurst, Michael Mackay, 2019, Behav. Inf. Technol..

Removing Human Bottlenecks in Bird Classification Using Camera Trap Images and Deep Learning

S. Longmore, S. Wich, P. Stephens, 2023, Remote. Sens..

Detection of Obstructive Sleep Apnoea Using Features Extracted From Segmented Time-Series ECG Signals With a One Dimensional Convolutional Neural Network

P. Fergus, C. Chalmers, Denis Reilly, 2024, IEEE Access.

Conservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology pdf

Paul Fergus, C. Aday Curbelo Montañez, Carl Chalmers, 2019, ArXiv.