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 …

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 …

Recent efforts to create a smart factory have inspired research that analyzes process data
collected from Internet of Things (IOT) sensors, to predict product quality in real time. This …

Fabric defect detection is a necessary and essential step of quality control in the textile
manufacturing industry. Traditional fabric inspections are usually performed by manual …

Fabric defect detection is an intriguing but challenging topic. Many methods have been
proposed for fabric defect detection, but these methods are still suboptimal due to the …

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 …

With the rise of labor costs and the advancement of automation in the textile industry, fabric
defect detection has become a hot research field in recent years. We proposed a learning …

Automatic detection of fabric defects is an important process for the textile industry. Besides
the detection accuracy, an automatic fabric defect detection solution for a resource-limited …

The defect detection task can be regarded as a realistic scenario of object detection in the
computer vision field and it is widely used in the industrial field. Directly applying vanilla …

Fabric inspection plays an important role in the process of quality control in textile
manufacturing. There is a growing demand in the textile industry to leverage computer vision …