PV systems are prone to external environmental conditions that affect PV system operations.
Visual inspection of the impacts of faults on PV system is considered a better practice rather …

Photovoltaic (PV) systems are subject to failures during their operation due to the aging
effects and external/environmental conditions. These faults may affect the different system …

Predicting crop yield based on the environmental, soil, water and crop parameters has been
a potential research topic. Deep-learning-based models are broadly used to extract …

A color image encryption algorithm using the Hénon-zigzag map and chaotic restricted
Boltzmann machine (CRBM) is proposed in this paper. The proposed pseudo-random …

Opinion summarization is a process to produce concise summaries from a large number of
opinionated texts. In this paper, we present a novel deep-learning-based method for the …

Cross-Domain Few-Shot Learning (CDFSL) aims for training an adaptable model that can
learn out-of-domain classes with a handful of samples. Compared to the well-studied few …

Meta-learning offers an effective solution to learn new concepts with scarce supervision
through an episodic training scheme: a series of target-like tasks sampled from base classes …

Energy-based models (EBMs) are experiencing a resurgence of interest in both the physics
community and the machine learning community. This article provides an intuitive …

Clustering ensemble is an unsupervised ensemble learning method that is very important in
machine learning, since it integrates multiple weak base clustering results to produce a …

Despite the successful use of Gaussian-binary restricted Boltzmann machines (GB-RBMs)
and Gaussian-binary deep belief networks (GB-DBNs), little is known about their theoretical …