2 citations · 3 across the 8 of their papers we have counts for
10 papers
AI Safety Considerations for Agents With Limited Time to Act
Leo Zeitler, Jack Richings, Victoria Nockles
In the wake of the increasingly public discussion about AI alignment, recent work has tried to propose specific AI architectures that behave safely. However, the proposed arguments…
The Turing Synthetic Radar Dataset: A dataset for pulse deinterleaving
Edward Gunn, Adam Hosford, Robert Jones +3
We present the Turing Synthetic Radar Dataset, a comprehensive dataset to serve both as a benchmark for radar pulse deinterleaving research and as an enabler of new research method…
Performance Decay in Deepfake Detection: The Limitations of Training on Outdated Data
Jack Richings, Margaux Leblanc, Ian Groves +1
The continually advancing quality of deepfake technology exacerbates the threats of disinformation, fraud, and harassment by making maliciously-generated synthetic content increasi…
Efficient SAR Vessel Detection for FPGA-Based On-Satellite Sensing
Colin Laganier, Liam Fletcher, Elim Kwan +2
Rapid analysis of satellite imagery within minutes-to-hours of acquisition is increasingly vital for many remote sensing applications, and is an essential component for developing…
Onboard Mission Replanning for Adaptive Cooperative Multi-Robot Systems
Elim Kwan, Rehman Qureshi, Liam Fletcher +3
Cooperative autonomous robotic systems have significant potential for executing complex multi-task missions across space, air, ground, and maritime domains. But they commonly opera…
SHARDeg: A Benchmark for Skeletal Human Action Recognition in Degraded Scenarios
Simon Malzard, Nitish Mital, Richard Walters +3
Computer vision (CV) models for detection, prediction or classification tasks operate on video data-streams that are often degraded in the real world, due to deployment in real-tim…
A Self-Supervised Framework for Space Object Behaviour Characterisation
Ian Groves, Andrew Campbell, James Fernandes +4
Foundation Models, which leverage large neural networks pre-trained on unlabelled data before fine-tuning for specific tasks, are increasingly being applied to specialised domains.…
Radar Pulse Deinterleaving with Transformer Based Deep Metric Learning
Edward Gunn, Adam Hosford, Daniel Mannion +3
When receiving radar pulses it is common for a recorded pulse train to contain pulses from many different emitters. The radar pulse deinterleaving problem is the task of separating…
Improving Object Detection by Modifying Synthetic Data with Explainable AI
Nitish Mital, Simon Malzard, Richard Walters +3
Limited real-world data severely impacts model performance in many computer vision domains, particularly for samples that are underrepresented in training. Synthetically generated…
2DSig-Detect: a semi-supervised framework for anomaly detection on image data using 2D-signatures
Xinheng Xie, Kureha Yamaguchi, Margaux Leblanc +4
The rapid advancement of machine learning technologies raises questions about the security of machine learning models, with respect to both training-time (poisoning) and test-time…