Accurate detection of tropical cyclones (TCs) is important to prevent and mitigate natural
disasters associated with TCs. Deep transfer learning methods have advantages in …

In recent years, many efforts have been made to develop efficient deep‐learning‐based
structural health monitoring (SHM) methods. Most of the proposed methods employ …

High‐quality and high‐fidelity removal of noise in the Electrocardiogram (ECG) signal is of
great significance to the auxiliary diagnosis of ECG diseases. In view of the single function of …

This paper proposes a novel data preprocessing method that converts numeric data into
representative graphs (polygons) expressing all of the relationships between data variables …

With the rapid development of machine learning technology, how to use machine learning
technology to empower the manufacturing industry has become a research hotspot. In order …

This paper proposes an innovative multi-output regression method that processes and
converts the numeric data variables into representative images (polygons) to build accurate …

The resource-constrained camera integrated Visual Sensor Networks (VSN) have
conquered numerous visual aided services from visual surveillance to habitat monitoring …

Recently, the evolution of Generative Adversarial Networks (GANs) has embarked on a
journey of revolutionizing the field of artificial and computational intelligence. To improve the …

Sky clouds affect solar observations significantly. Their shadows obscure the details of solar
features in observed images. Cloud-covered solar images are difficult to be used for further …

In this work, a novel semisupervised framework is proposed to tackle the small-sample
problem of dental-based human identification (DHI), achieving enhanced performance via a …