4 papers
Seeing enough: non-reference perceptual resolution selection for power-efficient client-side rendering
Yaru Liu, Dayllon VinÃcius Xavier Lemos, Ali Bozorgian +3
Many client-side applications, especially games, render video at high resolution and frame rate on power-constrained devices, even when users perceive little or no benefit from all…
Learning Confidence Bounds for Classification with Imbalanced Data
Matt Clifford, Jonathan Erskine, Alexander Hepburn +2
Class imbalance poses a significant challenge in classification tasks, where traditional approaches often lead to biased models and unreliable predictions. Undersampling and oversa…
Machine Learning for Climate Policy: Understanding Policy Progression in the European Green Deal
Patricia West, Michelle WL Wan, Alexander Hepburn +3
Climate change demands effective legislative action to mitigate its impacts. This study explores the application of machine learning (ML) to understand the progression of climate p…
Evaluating Perceptual Distance Models by Fitting Binomial Distributions to Two-Alternative Forced Choice Data
Alexander Hepburn, Raul Santos-Rodriguez, Javier Portilla
The Two Alternative Forced Choice (2AFC) paradigm offers advantages over the Mean Opinion Score (MOS) paradigm in psychophysics (PF), such as simplicity and robustness. However, wh…