114 citations · 250 across the 14 of their papers we have counts for
17 papers
Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics
Seyma Yucer, Amir Atapour Abarghouei, Noura Al Moubayed +1
Achieving an effective fine-grained appearance variation over 2D facial images, whilst preserving facial identity, is a challenging task due to the high complexity and entanglement…
Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking
Steven Carrell, Amir Atapour-Abarghouei
The use of mobiles phones when driving have been a major factor when it comes to road traffic incidents and the process of capturing such violations can be a laborious task. Advanc…
Resolving the cybersecurity Data Sharing Paradox to scale up cybersecurity via a co-production approach towards data sharing
Amir Atapour-Abarghouei, Andrew Stephen McGough, David Stanley Wall
As cybercriminals scale up their operations to increase their profits or inflict greater harm, we argue that there is an equal need to respond to their threats by scaling up cybers…
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks
John Brennan, Stephen Bonner, Amir Atapour-Abarghouei +3
With the growing significance of graphs as an effective representation of data in numerous applications, efficient graph analysis using modern machine learning is receiving a growi…
On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures
Matt Poyser, Amir Atapour-Abarghouei, Toby P. Breckon
Recent advances in generalized image understanding have seen a surge in the use of deep convolutional neural networks (CNN) across a broad range of image-based detection, classific…
Online Deep Reinforcement Learning for Autonomous UAV Navigation and Exploration of Outdoor Environments
Bruna G. Maciel-Pearson, Letizia Marchegiani, Samet Akcay +3
With the rapidly growing expansion in the use of UAVs, the ability to autonomously navigate in varying environments and weather conditions remains a highly desirable but as-of-yet…
Volenti non fit injuria: Ransomware and its Victims
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
With the recent growth in the number of malicious activities on the internet, cybersecurity research has seen a boost in the past few years. However, as certain variants of malware…
A Kings Ransom for Encryption: Ransomware Classification using Augmented One-Shot Learning and Bayesian Approximation
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
Newly emerging variants of ransomware pose an ever-growing threat to computer systems governing every aspect of modern life through the handling and analysis of big data. While var…
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation
Amir Atapour-Abarghouei, Toby P. Breckon
Robust three-dimensional scene understanding is now an ever-growing area of research highly relevant in many real-world applications such as autonomous driving and robotic navigati…
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions
Stephen Bonner, Amir Atapour-Abarghouei, Philip T Jackson +5
Graphs have become a crucial way to represent large, complex and often temporal datasets across a wide range of scientific disciplines. However, when graphs are used as input to ma…
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach
Amir Atapour-Abarghouei, Toby P. Breckon
Robust geometric and semantic scene understanding is ever more important in many real-world applications such as autonomous driving and robotic navigation. In this paper, we propos…
Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection
Samet Akçay, Amir Atapour-Abarghouei, Toby P. Breckon
Despite inherent ill-definition, anomaly detection is a research endeavor of great interest within machine learning and visual scene understanding alike. Most commonly, anomaly det…
Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
Nik Khadijah Nik Aznan, Amir Atapour-Abarghouei, Stephen Bonner +3
Despite significant recent progress in the area of Brain-Computer Interface (BCI), there are numerous shortcomings associated with collecting Electroencephalography (EEG) signals i…
Style Augmentation: Data Augmentation via Style Randomization
Philip T. Jackson, Amir Atapour-Abarghouei, Stephen Bonner +2
We introduce style augmentation, a new form of data augmentation based on random style transfer, for improving the robustness of convolutional neural networks (CNN) over both class…
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to 360° Panoramic Imagery
Grégoire Payen de La Garanderie, Amir Atapour Abarghouei, Toby P. Breckon
Recent automotive vision work has focused almost exclusively on processing forward-facing cameras. However, future autonomous vehicles will not be viable without a more comprehensi…
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
Samet Akcay, Amir Atapour-Abarghouei, Toby P. Breckon
Anomaly detection is a classical problem in computer vision, namely the determination of the normal from the abnormal when datasets are highly biased towards one class (normal) due…
Inspiring Computer Vision System Solutions
Julian Zilly, Amit Boyarski, Micael Carvalho +8
The "digital Michelangelo project" was a seminal computer vision project in the early 2000's that pushed the capabilities of acquisition systems and involved multiple people from d…