Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the
shortage of data monitoring devices and the difficulty of comprehensive coverage of …

Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

High quality product quality prediction is very important for iron and steel enterprises to
ensure stable production. However, most existing prediction methods are manually …

Deep Learning (DL) has achieved the great breakthrough in image classification. As DL
structure is problem-dependent and it has the crucial impact on its performance, it is still …

Convolutional neural networks (CNN) are highly effective for image classification and
computer vision activities. The accuracy of CNN architecture depends on the design and …

In recent years, deep learning has been applied to a variety of scenarios in Industrial
Internet of Things (IIoT), including enhancing the security of IIoT. However, the existing deep …

With increasing demand in many areas, materials are constantly evolving. However, they
still have numerous practical constraints. The rational design and discovery of new materials …

Side-scan sonar (SSS) is an essential acoustic sensor device for obtaining underwater
information. The instance segmentation of sonar images can effectively locate and detect …

Since pH can alter the biological functions, level of nutrients, wound healing process, and
the behavior of chemicals, various healthcare and food industries are showing increased …