Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

Abstract: Ensuring safe driving under real-time uncertainties remains a critical challenge in autonomous vehicle control. To address this issue for a collision avoidance task, this study proposes a ...

This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...

A collaboration between SISSA's Physics and Neuroscience groups has taken a step forward in understanding how memories are stored and retrieved in the ...

In our increasingly electrified world, supercapacitors have emerged as critical components in transportation and renewable energy systems, prized for their remarkable power density, cycling stability, ...

ABSTRACT: This paper studies recent assistive technologies and AI sound detection systems that have been developed to support both the safety and communication of individuals who are deaf. It ...

This study presents valuable computational findings on the neural basis of learning new motor memories and the savings using recurrent neural networks. The evidence supporting the claims of the ...

Abstract: Discrete time-varying problems are pervasive in the fields of engineering and science. Traditional handling schemes to discrete problem often involve the intervention of continuous-time ...