activity
20182022
most citedConservation AI: Live Stream Analysis for the Detection of Endangered Species Using Convolutional Neural Networks and Drone Technology

19 citations · 40 across the 8 of their papers we have counts for

collaborators

14 papers

cs.LG20221 cited

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

Paul Fergus, Carl Chalmers, William Henderson +2

Pressure ulcers are a challenge for patients and healthcare professionals. In the UK, 700,000 people are affected by pressure ulcers each year. Treating them costs the National Hea…

cs.LG20224 cited

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

Juliana Vélez, Paula J. Castiblanco-Camacho, Michael A. Tabak +3

Camera traps have transformed how ecologists study wildlife species distributions, activity patterns, and interspecific interactions. Although camera traps provide a cost-effective…

cs.LG20211 cited

Real-Time Predictive Maintenance using Autoencoder Reconstruction and Anomaly Detection

Sean Givnan, Carl Chalmers, Paul Fergus +2

Rotary machine breakdown detection systems are outdated and dependent upon routine testing to discover faults. This is costly and often reactive in nature. Real-time monitoring off…

cs.SD20211 cited

Modelling Animal Biodiversity Using Acoustic Monitoring and Deep Learning

C. Chalmers, P. Fergus, S. Wich +1

For centuries researchers have used sound to monitor and study wildlife. Traditionally, conservationists have identified species by ear; however, it is now common to deploy audio r…

eess.SP2020

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

Steven Thompson, Paul Fergus, Carl Chalmers +1

The study in this paper presents a one-dimensional convolutional neural network (1DCNN) model, designed for the automated detection of obstructive Sleep Apnoea (OSA) captured from…

cs.CV201919 cited

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

C. Chalmers, P. Fergus, Serge Wich +1

Many different species are adversely affected by poaching. In response to this escalating crisis, efforts to stop poaching using hidden cameras, drones and DNA tracking have been i…