Active vision dynamically refines spatiotemporal neural representations, optimising visual processing through scanning behaviour and non-associative learning, providing insights into efficient sensory ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...

Dynamic graph augmentation is used to improve the performance of dynamic GNNs. Most methods assume temporal locality, meaning that recent edges are more influential than earlier edges. However, for ...

Domain-adaptive vehicle re-identification is a challenging task that aims to transfer the knowledge from a labeled source domain to an unlabeled target domain for effective vehicle re-identification.

In the rapidly evolving landscape of higher education, traditional pedagogical methods often fall short in meeting the diverse needs and learning styles of students. This paper advocates for a ...

Future flying ad-hoc networks (FANETs) need to address issues related to delay and channel interference while ensuring high data transmission accuracy. In this letter, we propose a proximal policy ...

This paper presents an adaptive iterative learning control algorithm for a class of strict-feedback systems, which can achieve complete tracking with initial st ...