60 citations · 61 across the 5 of their papers we have counts for
5 papers
Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
Isaac Ronald Ward, Charles Moore, Kai Pak +2
Contrastive learning has recently demonstrated superior performance to supervised learning, despite requiring no training labels. We explore how contrastive learning can be applied…
Explainable Artificial Intelligence for Pharmacovigilance: What Features Are Important When Predicting Adverse Outcomes?
Isaac Ronald Ward, Ling Wang, Juan lu +3
Explainable Artificial Intelligence (XAI) has been identified as a viable method for determining the importance of features when making predictions using Machine Learning (ML) mode…
A Practical Tutorial on Graph Neural Networks
Isaac Ronald Ward, Jack Joyner, Casey Lickfold +2
Graph neural networks (GNNs) have recently grown in popularity in the field of artificial intelligence (AI) due to their unique ability to ingest relatively unstructured data types…
RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques
Isaac Ronald Ward, Hamid Laga, Mohammed Bennamoun
Object detection from RGB images is a long-standing problem in image processing and computer vision. It has applications in various domains including robotics, surveillance, human-…
Improving Image-Based Localization with Deep Learning: The Impact of the Loss Function
Isaac Ronald Ward, M. A. Asim K. Jalwana, Mohammed Bennamoun
This work investigates the impact of the loss function on the performance of Neural Networks, in the context of a monocular, RGB-only, image localization task. A common technique u…