22 citations · 22 across the 5 of their papers we have counts for
6 papers
Building Resilience to Out-of-Distribution Visual Data via Input Optimization and Model Finetuning
Christopher J. Holder, Majid Khonji, Jorge Dias +1
A major challenge in machine learning is resilience to out-of-distribution data, that is data that exists outside of the distribution of a model's training data. Training is often…
On the Application of Efficient Neural Mapping to Real-Time Indoor Localisation for Unmanned Ground Vehicles
Christopher J. Holder, Muhammad Shafique
Global localisation from visual data is a challenging problem applicable to many robotics domains. Prior works have shown that neural networks can be trained to map images of an en…
On Efficient Real-Time Semantic Segmentation: A Survey
Christopher J. Holder, Muhammad Shafique
Semantic segmentation is the problem of assigning a class label to every pixel in an image, and is an important component of an autonomous vehicle vision stack for facilitating sce…
Camera Bias in a Fine Grained Classification Task
Philip T. Jackson, Stephen Bonner, Ning Jia +3
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a mode…
Multi-Task Regression-based Learning for Autonomous Unmanned Aerial Vehicle Flight Control within Unstructured Outdoor Environments
Bruna G. Maciel-Pearson, Samet Akcay, Amir Atapour-Abarghouei +2
Increased growth in the global Unmanned Aerial Vehicles (UAV) (drone) industry has expanded possibilities for fully autonomous UAV applications. A particular application which has…
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network
Christopher J. Holder, Toby P. Breckon, Xiong Wei
Scene understanding for autonomous vehicles is a challenging computer vision task, with recent advances in convolutional neural networks (CNNs) achieving results that notably surpa…