3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2020★ 1 cited
The Utility of Decorrelating Colour Spaces in Vector Quantised Variational Autoencoders
Arash Akbarinia, Raquel Gil-Rodríguez, Alban Flachot +1
Vector quantised variational autoencoders (VQ-VAE) are characterised by three main components: 1) encoding visual data, 2) assigning different vectors in the so-called embeddin…
cs.CV2019★ 3 cited
Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar
Arash Akbarinia, Karl R. Gegenfurtner
Machine learning is advancing towards a data-science approach, implying a necessity to a line of investigation to divulge the knowledge learnt by deep neuronal networks. Limiting t…
cs.CV2019★ 1 cited
Manifestation of Image Contrast in Deep Networks
Arash Akbarinia, Karl R. Gegenfurtner
Contrast is subject to dramatic changes across the visual field, depending on the source of light and scene configurations. Hence, the human visual system has evolved to be more se…