Recently, there are many works on discriminant analysis, which promote the robustness of
models against outliers by using L 1-or L 2, 1-norm as the distance metric. However, both of …

In this paper, a deep-learning-based driver-drowsiness detection for brain-computer
interface (BCI) using functional near-infrared spectroscopy (fNIRS) is investigated. The …

Recently, many convolutional neural network (CNN) methods have been designed for
hyperspectral image (HSI) classification since CNNs are able to produce good …

In this article, a deep probability model, called the discriminative mixture variational
autoencoder (DMVAE), is developed for the feature extraction in semisupervised learning …

Abstract Domain adaptation algorithms leverage the knowledge from a well-labeled source
domain to facilitate the learning of an unlabeled target domain, in which the source domain …

With the advent of neural network, unprecedented advancements have been achieved in
many tasks, including radar signal processing. However, a key disadvantage of the current …

One of the radar high resolution range profile (HRRP) target recognition issues is the
existence of noise interference, especially for the ground target. The recognition …

Abstract The abstraction of Brain Computer Interface (BCI) is a communication and control
system that translated human mind thoughts into real-world interaction without any use of …

Brain-computer interface (BCI) is one of the technologies that help people with impairment.
Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive tool frequently used for BCI …

Blurred vision images caused by rainy weather can negatively influence the performance of
outdoor vision systems. Therefore, it is necessary to remove rain streaks from single image …