Defects in the textile manufacturing process lead to a great waste of resources and further
affect the quality of textile products. Automated quality guarantee of textile fabric materials is …

Fabric defect detection plays a crucial role in fabric inspection and quality control.
Convolutional neural networks (CNNs)-based model has been proved successful in various …

Fabric defect detection is the important step of ensuring the quality and price of textiles. In
order to make the automatic fabric defect detection system used in production sites, a cloud …

Deep learning (DL) algorithms have demonstrated a high ability to perform speedy and
accurate COVID-19 diagnosis utilizing computed tomography (CT) and X-Ray scans. The …

Alzheimer's disease (AD) is the type of dementia that affects the world's significant
population and is expected to be increased worldwide. In recent years, the main focus of …

This work proposes a novel hybrid signal processing technique to extract information on
disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of …

Detecting and classifying the Pap smear cell images is important task for cervical cancer
identification. In this article, dual tree complex wavelet transform (DTCWT) based modified …

In this work, the most promising ultrasonic signal processing methods—discrete wavelet
transform, variational mode decomposition and Hilbert transform—are applied for the …

Ultrasonic non-destructive testing (NDT) methods are being used quite effectively
nowadays, but the multilayered structure of composite materials results in the serious …

In recent times, vehicle type classification (VTC) is considered important for intelligent
transport system. The VTC is a challenging research topic, due to the factors like minimum …