114 citations · 579 across the 79 of their papers we have counts for
10 papers · 1 filter
Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery
Jack. W. Barker, Neelanjan Bhowmik, Toby. P. Breckon
Within commercial wind energy generation, the monitoring and predictive maintenance of wind turbine blades in-situ is a crucial task, for which remote monitoring via aerial survey…
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes
Sam Bond-Taylor, Peter Hessey, Hiroshi Sasaki +2
Whilst diffusion probabilistic models can generate high quality image content, key limitations remain in terms of both generating high-resolution imagery and their associated high…
Progressively Select and Reject Pseudo-labelled Samples for Open-Set Domain Adaptation
Qian Wang, Fanlin Meng, Toby P. Breckon
Domain adaptation solves image classification problems in the target domain by taking advantage of the labelled source data and unlabelled target data. Usually, the source and targ…
Measuring Hidden Bias within Face Recognition via Racial Phenotypes
Seyma Yucer, Furkan Tektas, Noura Al Moubayed +1
Recent work reports disparate performance for intersectional racial groups across face recognition tasks: face verification and identification. However, the definition of those rac…
Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery
Thomas W. Webb, Neelanjan Bhowmik, Yona Falinie A. Gaus +1
The recent advancement in deep Convolutional Neural Network (CNN) has brought insight into the automation of X-ray security screening for aviation security and beyond. Here, we exp…
On the impact of using X-ray energy response imagery for object detection via Convolutional Neural Networks
Neelanjan Bhowmik, Yona Falinie A. Gaus, Toby P. Breckon
Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited…
PANDA : Perceptually Aware Neural Detection of Anomalies
Jack W. Barker, Toby P. Breckon
Semi-supervised methods of anomaly detection have seen substantial advancement in recent years. Of particular interest are applications of such methods to diverse, real-world anoma…
UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Models
Hiroshi Sasaki, Chris G. Willcocks, Toby P. Breckon
We propose a novel unpaired image-to-image translation method that uses denoising diffusion probabilistic models without requiring adversarial training. Our method, UNpaired Image…
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-identification in Video Imagery
Daniel Organisciak, Matthew Poyser, Aishah Alsehaim +4
As unmanned aerial vehicles (UAVs) become more accessible with a growing range of applications, the potential risk of UAV disruption increases. Recent development in deep learning…
Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark
Brian K. S. Isaac-Medina, Matt Poyser, Daniel Organisciak +3
Unmanned Aerial Vehicles (UAV) can pose a major risk for aviation safety, due to both negligent and malicious use. For this reason, the automated detection and tracking of UAV is a…