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 …

Wood defects are quickly identified from an optical image based on deep learning
methodology, which effectively improves the wood utilization. The traditional neural network …

Blind people often encounter challenges in managing their clothing, specifically in
identifying defects such as stains or holes. With the progress of the computer vision field, it is …

This paper develops a secure multimodal fusion system to authenticate the users of E-
correction systems in educational institutions. The system is based on hand geometry and …

For any industry, an important part of quality control is the detection and identification of
defects of the products. During the manufacturing process, a wide range of defects occur on …

Demands for minimum parameter setup in machine learning models are desirable to avoid
time-consuming optimization processes. The k-Nearest Neighbors is one of the most …

This study presents an innovative machine learning (ML) approach to predicting raw
material yield in the leather tanning industry, addressing a critical challenge in production …

As part of industrial quality control in the leather industry, it is important to identify the
abnormal features in wet-blue leather samples. Manual inspection of leather samples is the …

Automated leather defect classification has gained a lot of attention in recent years with the
advancement of automation in the leather industry. In recent years a plethora of new …

The coronavirus or COVID-19 infectious virus is the deadliest and potentially dangerous
disease for humans. Radiologists frequently employ medical imaging tools to visualize …