Most of the application domain suffers from not having sufficient labeled data whereas
unlabeled data is available cheaply. To get labeled instances, it is very difficult because …

Common spatial pattern (CSP)-based spatial filtering has been most popularly applied to
electroencephalogram (EEG) feature extraction for motor imagery (MI) classification in brain …

This article studies the formation tracking problem of a team of autonomous underwater
vehicles (AUVs) with the ocean current disturbances. A distributed Lyapunov-based model …

Unlike the visual object tracking, thermal infrared object tracking can track a target object in
total darkness. Therefore, it has broad applications, such as in rescue and video …

Deep convolutional neural networks (CNNs) have contributed to the significant progress of
the single-image super-resolution (SISR) field. However, the majority of existing CNN-based …

Hyperspectral image (HSI) denoising has been attracting much research attention in remote
sensing area due to its importance in improving the HSI qualities. The existing HSI …

Abstract Broad Learning System (BLS) has achieved outstanding performance in
classification and regression problems. Specifically, the accuracy and efficiency can be …

The goal of learning-based image super resolution (SR) is to generate a plausible and
visually pleasing high-resolution (HR) image from a given low-resolution (LR) input. The SR …

Recovering the image corrupted by additive white Gaussian noise (AWGN) and impulse
noise is a challenging problem due to its difficulties in an accurate modeling of the …

The performance of traditional face recognition systems is sharply reduced when
encountered with a low-resolution (LR) probe face image. To obtain much more detailed …