118 citations · 221 across the 10 of their papers we have counts for
12 papers
HuMemSLAM: Efficient Human-Inspired Semantic Place Recognition for Robust Visual SLAM
Mayowa Adebambo, Sebastian Donnelly, Armand Amaritei +2
Autonomous systems require reliable place recognition for efficient and effective simultaneous localisation and mapping (SLAM). Traditional geometric visual SLAM approaches rely on…
PathSpace: Rapid continuous map approximation for efficient SLAM using B-Splines in constrained environments
Aduen Benjumea, Andrew Bradley, Alexander Rast +1
Simultaneous Localization and Mapping (SLAM) plays a crucial role in enabling autonomous vehicles to navigate previously unknown environments. Semantic SLAM mostly extends visual S…
(hu)Man vs. Machine: In the Future of Motorsport, can Autonomous Vehicles Compete?
Armand Amaritei, Amber-Lily Blackadder, Sebastian Donnelly +5
Motorsport has historically driven technological innovation in the automotive industry. Autonomous racing provides a proving ground to push the limits of performance of autonomous…
SEG-JPEG: Simple Visual Semantic Communications for Remote Operation of Automated Vehicles over Unreliable Wireless Networks
Sebastian Donnelly, Ruth Anderson, George Economides +4
Remote Operation is touted as being key to the rapid deployment of automated vehicles. Streaming imagery to control connected vehicles remotely currently requires a reliable, high…
Temporal DINO: A Self-supervised Video Strategy to Enhance Action Prediction
Izzeddin Teeti, Rongali Sai Bhargav, Vivek Singh +3
The emerging field of action prediction plays a vital role in various computer vision applications such as autonomous driving, activity analysis and human-computer interaction. Des…
A Scenario-Based Functional Testing Approach to Improving DNN Performance
Hong Zhu, Thi Minh Tam Tran, Aduen Benjumea +1
This paper proposes a scenario-based functional testing approach for enhancing the performance of machine learning (ML) applications. The proposed method is an iterative process th…
Simulating Malicious Attacks on VANETs for Connected and Autonomous Vehicle Cybersecurity: A Machine Learning Dataset
Safras Iqbal, Peter Ball, Muhammad H Kamarudin +1
Connected and Autonomous Vehicles (CAVs) rely on Vehicular Adhoc Networks with wireless communication between vehicles and roadside infrastructure to support safe operation. Howeve…
Vision in adverse weather: Augmentation using CycleGANs with various object detectors for robust perception in autonomous racing
Izzeddin Teeti, Valentina Musat, Salman Khan +3
In an autonomous driving system, perception - identification of features and objects from the environment - is crucial. In autonomous racing, high speeds and small margins demand r…
YOLO-Z: Improving small object detection in YOLOv5 for autonomous vehicles
Aduen Benjumea, Izzeddin Teeti, Fabio Cuzzolin +1
As autonomous vehicles and autonomous racing rise in popularity, so does the need for faster and more accurate detectors. While our naked eyes are able to extract contextual inform…
Worsening Perception: Real-time Degradation of Autonomous Vehicle Perception Performance for Simulation of Adverse Weather Conditions
Ivan Fursa, Elias Fandi, Valentina Musat +7
Autonomous vehicles rely heavily upon their perception subsystems to see the environment in which they operate. Unfortunately, the effect of variable weather conditions presents a…
ROAD: The ROad event Awareness Dataset for Autonomous Driving
Gurkirt Singh, Stephen Akrigg, Manuele Di Maio +13
Humans drive in a holistic fashion which entails, in particular, understanding dynamic road events and their evolution. Injecting these capabilities in autonomous vehicles can thus…
Real-Time Optimal Trajectory Planning for Autonomous Vehicles and Lap Time Simulation Using Machine Learning
Sam Garlick, Andrew Bradley
Widespread development of driverless vehicles has led to the formation of autonomous racing, where technological development is accelerated by the high speeds and competitive envir…