The brain exhibits a complex temporal structure which translates into a hierarchy of distinct
neural timescales. An open question is how these intrinsic timescales are related to sensory …

Assessing residual consciousness and cognitive abilities in unresponsive patients is a
major clinical concern and a challenge for cognitive neuroscience. Although neuroimaging …

Speed plays a significant role in evaluating the evolution of traffic status, and predicting
speed is one of the fundamental tasks for the intelligent transportation system. There exists a …

A vehicle’s license plate is the unique feature by which to identify each individual vehicle. As
an important research area of an intelligent transportation system, the recognition of vehicle …

There have been many attempts to design brain–computer interfaces (BCIs) for wheelchair
control based on steady state visual evoked potential (SSVEP), event-related …

A learning automaton (LA) is a powerful tool for reinforcement learning. Its action probability
vector plays two roles: 1) deciding when it converges, ie, total computing budget it has used, …

Consciousness is a mental characteristic of the human mind, whose exact neural features
remain unclear. We aimed to identify the critical nodes within the brain's global functional …

Our brain processes the different timescales of our environment's temporal input stochastics.
Is such a temporal input processing mechanism key for consciousness? To address this …

Locating multiple sources in an unknown environment based on their signal strength is called
a multi-source location problem. In recent years, there has been great interest in deploying …

In this paper, we present a new approach to detect traffic signs based on cascaded convolutional
neural networks (CNNs). First, the local binary pattern (LBP) feature detector and the …