54 citations · 211 across the 34 of their papers we have counts for
4 papers · 2 filters
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…
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video
Miguel Jaques, Michael Burke, Timothy Hospedales
We propose a model that is able to perform unsupervised physical parameter estimation of systems from video, where the differential equations governing the scene dynamics are known…
Detecting inter-sectional accuracy differences in driver drowsiness detection algorithms
Mkhuseli Ngxande, Jule-Raymond Tapamo, Michael Burke
Convolutional Neural Networks (CNNs) have been used successfully across a broad range of areas including data mining, object detection, and in business. The dominance of CNNs follo…
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…