Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …

Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

In this paper, we introduce the Layer-Peeled Model, a nonconvex, yet analytically tractable,
optimization program, in a quest to better understand deep neural networks that are trained …

MusiteDeep is an online resource providing a deep-learning framework for protein post-
translational modification (PTM) site prediction and visualization. The predictor only uses …

Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …

Motor Imagery Brain-Computer Interfaces (MI-BCIs) are AI-driven systems that capture brain
activity patterns associated with mental imagination of movement and convert them into …

When interacting with technical systems, users experience mental workload. Particularly in
multitasking scenarios (eg, interacting with the car navigation system while driving) it is …

In the previous decade, breakthroughs in the central nervous system bioinformatics and
computational innovation have prompted significant developments in brain–computer …

Spiking neural networks (SNNs) serve as a promising computational framework for
integrating insights from the brain into artificial intelligence (AI). Existing software …

Fruit traits such as cluster compactness, fruit maturity, and berry number per clusters are
important to blueberry breeders and producers for making informed decisions about …