Vibration signals play a key role in machinery fault diagnosis, which are often buried by
strong noises due to complex working conditions. Typical deep neural networks (eg …

Utilizing signal processing tools in deep learning models has been drawing increasing
attention. Fourier transform (FT), one of the most popular signal processing tools, is …

In contemporary cities, road collapse is one of the most common disasters. This study
proposed a framework for assessing the risk of urban road collapse. The framework first …

Accurately sensing the main bearing state and diagnosing fault types is crucial to ensure the
safe operation of the main drive system of tunnel boring machines. Currently, the research …

The success of the convolutional neural network (CNN) comes with a tremendous growth of
diverse CNN structures, making it hard to deploy on limited-resource platforms. These over …

Existing learned-based image compression methods have shown impressive performance.
However, they rely mostly on the consistent distribution between training and test images …