Remote sensing image scene classification aims to commit the semantic labels according to
the content of images. Convolutional Neural Network (CNN) is often used here to extract …

Under the background of circular economy, sustainable development is no longer a slogan
but an action. Many countries gradually attach importance to promoting green development …

This paper presents a theoretical derivation of two new graph-based regularization methods
for fusing the individual results of multiple detectors (two-class classifiers). The proposed …

Dempster–Shafer evidence theory (DSET) is extensively employed in multi-source data
fusion applications. Nonetheless, when belief probability assignments (BPAs) exhibit …

Data fusion technology plays a pivotal role in aggregating, storing, and mining multi-source
data to extract its joint value through the construction of a unified fusion representation …

Evidential reasoning (ER) rule has been widely used in the fields of information fusion,
multiattribute decision making, and pattern recognition. In current studies of ER rule, there is …

The key task of fault diagnosis is to establish the nonlinear mapping relationship between
fault feature sequences (FFSs) and fault modes (FMs). Therefore, it is usually necessary to …

In this paper, a novel method of using deep learning to construct a digital twin of the thermos-
compression bonding blades temperature field is presented. Usually, a heat transfer model …

针对汽车操纵稳定性试验评价指标自动化处理需要自动识别试验类型的需求,
提出一种基于卷积神经网络的汽车操纵稳定性试验类型自动分类方法. 在分析汽车操纵稳定性 …

In the process industry, an alarm system is one of the important ways of condition
monitoring. Due to the complexity and irregularity of process information in condition …