There are different applications of computer vision and digital image processing in various
applied domains and automated production process. In textile industry, fabric defect …

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 …

Visual inspection is a main stage of quality control process in many applications. Surface
defect inspection plays an important role in fabric textile quality control systems. Each type of …

Ensuring product quality and integrity is paramount in the rapidly evolving landscape of
industrial manufacturing. Although effective to a certain degree, traditional quality control …

Defects on the surface of yarn-dyed fabrics are one of the important factors affecting the
quality of fabrics. Defect detection is the core link of quality control. Due to the diversity of …

Detection of surface defects in manufacturing systems is crucial for product quality. Detection
of surface defects with high accuracy can prevent financial and time losses. Recently, efforts …

Steel is a basic material, and vision-based defect recognition is important for quality.
Recently, deep learning, especially convolutional neural network (CNN), has become a …

Class imbalance is a key issue affecting the performance of computer vision applications
such as medical image analysis, objection detection and recognition, image segmentation …

The detection of water bodies from satellite images plays a vital role in research
development. It has a wide range of applications such as the prediction of natural disasters …

The use of the deep learning approach in the textile industry for the purpose of defect
detection has become an increasing trend in the past 20 years. The majority of publications …