Zobrazeno 1 - 10
of 911
pro vyhledávání: '"Bradley Andrew"'
Autor:
Khan, Salman, Teeti, Izzeddin, Alitappeh, Reza Javanmard, Stoian, Mihaela C., Giunchiglia, Eleonora, Singh, Gurkirt, Bradley, Andrew, Cuzzolin, Fabio
Autonomous Vehicle (AV) perception systems require more than simply seeing, via e.g., object detection or scene segmentation. They need a holistic understanding of what is happening within the scene for safe interaction with other road users. Few dat
Externí odkaz:
http://arxiv.org/abs/2411.01683
Interpretation and understanding of video presents a challenging computer vision task in numerous fields - e.g. autonomous driving and sports analytics. Existing approaches to interpreting the actions taking place within a video clip are based upon T
Externí odkaz:
http://arxiv.org/abs/2310.17493
Autor:
Teeti, Izzeddin, Bhargav, Rongali Sai, Singh, Vivek, Bradley, Andrew, Banerjee, Biplab, Cuzzolin, Fabio
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. Despite significant advancements, accurately predicting future actions re
Externí odkaz:
http://arxiv.org/abs/2308.04589
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 that starts with testing the ML model on various scenarios to identify a
Externí odkaz:
http://arxiv.org/abs/2307.07083
Autor:
Mitchell, Emily G., Dryden, Ian L., Fallaize, Christopher J., Andersen, Roxane, Bradley, Andrew V., Large, David J., Sowter, Andrew
Peatlands account for 10% of UK land area, 80% of which are degraded to some degree, emitting carbon at a similar magnitude to oil refineries or landfill sites. A lack of tools for rapid and reliable assessment of peatland condition has limited monit
Externí odkaz:
http://arxiv.org/abs/2209.14187
There are strong incentives to build models that demonstrate outstanding predictive performance on various datasets and benchmarks. We believe these incentives risk a narrow focus on models and on the performance metrics used to evaluate and compare
Externí odkaz:
http://arxiv.org/abs/2206.02157
Connected and Autonomous Vehicles (CAVs) rely on Vehicular Adhoc Networks with wireless communication between vehicles and roadside infrastructure to support safe operation. However, cybersecurity attacks pose a threat to VANETs and the safe operatio
Externí odkaz:
http://arxiv.org/abs/2202.07704
Autor:
Teeti, Izzeddin, Musat, Valentina, Khan, Salman, Rast, Alexander, Cuzzolin, Fabio, Bradley, Andrew
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 rapid and accurate detection systems. During the race, the weather can
Externí odkaz:
http://arxiv.org/abs/2201.03246
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 information almost instantly, even from far away, image resolution and compu
Externí odkaz:
http://arxiv.org/abs/2112.11798
