Abstract: The traditional deep learning-based bearing fault diagnosis approaches assume that the training and test data follow the same distribution. This assumption, however, is not always true for ...

Abstract: Pansharpening aims at fusing a panchromatic image with a multispectral one, to generate an image with the high spatial resolution of the former and the high spectral resolution of the latter ...

Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it ...

Abstract: Alternative vehicles, such as plug-in hybrid electric vehicles, are becoming more popular. The batteries of these plug-in hybrid electric vehicles are to be charged at home from a standard ...

Abstract: Water quality prediction (WQP) plays an essential role in water quality management for aquaculture to make aquaculture production profitable and sustainable. In this work, we propose hybrid ...

Abstract: Spiking neural networks (SNNs) are nature's versatile solution to fault-tolerant, energy-efficient signal processing. To translate these benefits into hardware, a growing number of ...

Abstract: We present a comprehensive study and evaluation of existing single-image dehazing algorithms, using a new large-scale benchmark consisting of both synthetic and real-world hazy images, ...

Abstract: High power conversion efficiency (PCE) flexible perovskite solar cells (FPSCs) are highly desired power sources for aerospace crafts and flexible electronics. However, their PCEs still lag ...

Abstract: Research on robotic exoskeletons has rapidly expanded over the previous decade. Advances in robotic hardware and energy supplies have enabled viable prototypes for human testing. This review ...

Abstract: The convergence of deep learning and Big Data has spurred significant interest in developing novel hardware that can run large artificial intelligence (AI) workloads more efficiently. Over ...

Abstract: Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D LiDAR data has led to rapid development in the field of autonomous driving. However, automated ...

Abstract: This paper presents a barrier Lyapunov function based nonsingular fast terminal sliding mode control with fixed-time non-recursive disturbance observer for the blended-wing-body (BWB) ...