Electroencephalogram (EEG) signals have been utilized in a variety of medical as well as
engineering applications. However, one of the challenges associated with recording EEG …

The imbalanced development between deep learning-based model design and motor
imagery (MI) data acquisition raises concerns about the potential overfitting issue—models …

Intelligent fault diagnosis, detection, and prognostics (DDP) for complex equipment
prognostics and health management (PHM) have achieved remarkable breakthroughs …

Digital Transformation integrates information technology across a broad spectrum of
industrial sectors. Industrial Cyber-Physical Systems (ICPS) play a vital role in this …

Vibration signals are widely applied in mechanical fault diagnosis methods. Strong and
nonstationary noise can easily affect the vibration signals, and the vibration signals will differ …

Electroencephalographic (EEG) signals are acquired non-invasively from electrodes placed
on the scalp. Experts in the field can use EEG signals to distinguish between patients with …

The performance of data driven-based intelligent diagnosis method greatly depends on the
quantity and quality of data. Nevertheless, due to realistic limitations, failure data is hard to …

Recently, there has been significant growth in the number of initiatives aimed at increasing,
establishing, and managing RES. Polluting, degrading, and adding to the greenhouse effect …

Series arc fault is the main cause of electrical fire in low-voltage distribution system. A fast
and accurate detection system can reduce the risk of fire effectively. In this paper, series arc …

随着监控视频的覆盖越来越广泛, 人们对于智能视频算法的需求量也越来越大.
在这个以深度学习算法模型为主流的时代, 数据显得尤为重要. 在很多小众场景中 …