There is increasing evidence that the brain relies on a set of canonical neural computations,
repeating them across brain regions and modalities to apply similar operations to different …

Does the brain use a firing rate code or a spike timing code? Considering this controversial
question from an epistemological perspective, I argue that progress has been hampered by …

We compare the robustness of humans and current convolutional deep neural networks
(DNNs) on object recognition under twelve different types of image degradations. First, using …

We propose a referenceless perceptual fog density prediction model based on natural
scene statistics (NSS) and fog aware statistical features. The proposed model, called Fog …

Current state-of-the-art object recognition models are largely based on convolutional neural
network (CNN) architectures, which are loosely inspired by the primate visual system …

We propose a natural scene statistic-based distortion-generic blind/no-reference (NR)
image quality assessment (IQA) model that operates in the spatial domain. The new model …

Neuroscience research has exploded, with more than fifty thousand neuroscientists applying
increasingly advanced methods. A mountain of new facts and mechanisms has emerged …

In the mammalian cerebral cortex the diversity of interneuronal subtypes underlies a division
of labour subserving distinct modes of inhibitory control,,,,,,. A unique mode of inhibitory …

In this paper we propose a new no-reference (NR) image quality assessment (IQA) metric
using the recently revealed free-energy-based brain theory and classical human visual …

Human visual object recognition is typically rapid and seemingly effortless, as well as largely
independent of viewpoint and object orientation. Until very recently, animate visual systems …