1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2019
Bias Remediation in Driver Drowsiness Detection systems using Generative Adversarial Networks
Mkhuseli Ngxande, Jules-Raymond Tapamo, Michael Burke
Datasets are crucial when training a deep neural network. When datasets are unrepresentative, trained models are prone to bias because they are unable to generalise to real world s…
cs.CV2019★ 1 cited
DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis
Mkhuseli Ngxande, Jules-Raymond Tapamo, Michael Burke
Recent work has shown significant progress in the direction of synthetic data generation using Generative Adversarial Networks (GANs). GANs have been applied in many fields of comp…
cs.CV2014★ 1 cited
Single camera pose estimation using Bayesian filtering and Kinect motion priors
Michael Burke, Joan Lasenby
Traditional approaches to upper body pose estimation using monocular vision rely on complex body models and a large variety of geometric constraints. We argue that this is not idea…