Traditional machine learning (ML) techniques such as support vector machine, logistic
regression, and artificial neural network have been applied most frequently in water quality …

High-dimensional features are extensively accessible in machine learning and computer
vision areas. How to learn an efficient feature representation for specific learning tasks is …

Multimodal learning mines and analyzes multimodal data in reality to better understand and
appreciate the world around people. However, how to exploit this rich multimodal data …

Today's smart city infrastructure is predominantly dependant on Internet of Things (IoT)
technologies. IoT technology essentially facilitates a platform for service automation through …

This article proposes a novel segmentation algorithm for synthetic aperture radar (SAR)
images. The algorithm performs region-level segmentation based on edge feature and label …

Satellite images are more accessible with the increase of commercial satellites being
orbited. These images are used in a wide range of applications including agricultural …

Oil remains the most important energy source in the world today, and tankers are its main
modes of transportation. However, there is a high risk of oil spills, which can cause serious …

The high dimensionality and sparsity of data often increase the complexity of clustering;
these factors occur simultaneously in unsupervised learning. Clustering and linear …

Recently, the restricted Boltzmann machine (RBM) has aroused considerable interest in the
multiview learning field. Although effectiveness is observed, like many existing multiview …

Abstract Restricted Boltzmann machines (RBMs) have received considerable research
interest in recent years because of their capability to discover latent representations in an …