52 citations · 90 across the 6 of their papers we have counts for
6 papers
Generative Adversarial Networks for Non-Raytraced Global Illumination on Older GPU Hardware
Jared Harris-Dewey, Richard Klein
We give an overview of the different rendering methods and we demonstrate that the use of a Generative Adversarial Networks (GAN) for Global Illumination (GI) gives a superior qual…
Automated Parking Space Detection Using Convolutional Neural Networks
Julien Nyambal, Richard Klein
Finding a parking space nowadays becomes an issue that is not to be neglected, it consumes time and energy. We have used computer vision techniques to infer the state of the parkin…
Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing
Pierce Burke, Richard Klein
With the increased interest in machine learning and big data problems, the need for large amounts of labelled data has also grown. However, it is often infeasible to get experts to…
The Wits Intelligent Teaching System: Detecting Student Engagement During Lectures Using Convolutional Neural Networks
Richard Klein, Turgay Celik
To perform contingent teaching and be responsive to students' needs during class, lecturers must be able to quickly assess the state of their audience. While effective teachers are…
Explicit homography estimation improves contrastive self-supervised learning
David Torpey, Richard Klein
The typical contrastive self-supervised algorithm uses a similarity measure in latent space as the supervision signal by contrasting positive and negative images directly or indire…
Quantisation and Pruning for Neural Network Compression and Regularisation
Kimessha Paupamah, Steven James, Richard Klein
Deep neural networks are typically too computationally expensive to run in real-time on consumer-grade hardware and low-powered devices. In this paper, we investigate reducing the…