30 citations · 66 across the 7 of their papers we have counts for
7 papers
DIRA-SS:Dynamic Domain Incremental Regularised Adaptation -- Self-Supervised
Abanoub Ghobrial, Kerstin Eder
Autonomous systems (AS) often rely on Deep Neural Network (DNN) classifiers to operate in complex and dynamically changing environments. However, during operation, these classifier…
Evaluation Metrics for DNNs Compression
Abanoub Ghobrial, Samuel Budgett, Dieter Balemans +3
There is a lot of ongoing research effort into developing different techniques for neural networks compression. However, the community lacks standardised evaluation metrics, which…
A Trustworthiness Score to Evaluate DNN Predictions
Abanoub Ghobrial, Darryl Hond, Hamid Asgari +1
Due to the black box nature of deep neural networks (DNN), the continuous validation of DNN during operation is challenging with the absence of a human monitor. As a result this ma…
DIRA: Dynamic Domain Incremental Regularised Adaptation
Abanoub Ghobrial, Xuan Zheng, Darryl Hond +2
Autonomous systems (AS) often use Deep Neural Network (DNN) classifiers to allow them to operate in complex, high-dimensional, non-linear, and dynamically changing environments. Du…
Safety Validation of Autonomous Vehicles using Assertion Checking
Christopher Harper, Greg Chance, Abanoub Ghobrial +3
Safety and mission performance validation of autonomous vehicles (AVs) is a major challenge. In this paper we describe a methodology for constructing and applying assertion checks…
On Determinism of Game Engines used for Simulation-based Autonomous Vehicle Verification
Greg Chance, Abanoub Ghobrial, Kevin McAreavey +3
Game engines are increasingly used as simulation platforms by the autonomous vehicle (AV) community to develop vehicle control systems and test environments. A key requirement for…
An Agency-Directed Approach to Test Generation for Simulation-based Autonomous Vehicle Verification
Greg Chance, Abanoub Ghobrial, Severin Lemaignan +2
Simulation-based verification is beneficial for assessing otherwise dangerous or costly on-road testing of autonomous vehicles (AV). This paper addresses the challenge of efficient…