The use of image processing for the detection and classification of defects has been a reality
for some time in science and industry. New methods are continually being presented to …

This paper provides a comprehensive review of automatic recognition of woven fabric
structural parameters in recent years. Fabric structural parameters mainly include fabric …

Inspection of dry carbon textiles is a key step to ensure quality in aerospace manufacturing.
Due to the rarity and variety of defects, collecting a comprehensive defect dataset is difficult …

Numerous industrial applications of machine learning feature critical issues that need to be
addressed. This work proposes a framework to deal with these issues, such as competing …

Fabric anomaly detection (AD) tries to detect anomalies (ie, defects) in fabrics, and fabric AD
approaches are continuously improved with respect to their AD performance. However …

With the fast progress of computer science and image processing technologies, computer
vision technology has been applied largely in the textile industry. Consequently, the …

Inspection is the most important role in textile industry which declares the quality of the
apparel product. Many Industries were improving their production or quality using Artificial …

In terms of quality control, manual inspection of the fabric is time-consuming and inefficient.
In this work, we are studying several models of deep convolutional neural networks …

Technological advancements, including automation and artificial intelligence, have
significantly influenced the textile and apparel sector by improving efficiency, productivity …

Over the last decade, considerable progress has been made in the image processing of
textile materials. First, this dissertation provides a detailed discussion of the present, past …