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 …

Object detection and classification denotes one of the most extensively-utilized machine
vision applications given the high requirements put forward for object classification and …

Fabric defect detection is a crucial problem in the production of textile industry. Nowadays, a
large number of fabric defect detection algorithms based on deep learning have been …

In recent times, deep learning frameworks have become the preferred solution for visual
object detection tasks, including texture defect detection. However, in real-world industrial …

Featured Application The research results can quickly and accurately detect defects in the
fabric production process. Abstract The generation of defects during fabric production …

For fabric defect detection, the crucial issue is that large defects can be detected but not
small ones, and vice versa, and this symmetric contradiction cannot be solved by a single …

Defects on fabric surfaces are difficult to identify owing to unsuitable computing devices,
highly complex algorithms, small size, and high degree of integration with the fabric. To this …

Due to the little variation in defect points, tile block defect detection typically detects subtle
defects in large-format images, allowing defective characteristics to be displayed regionally …

Fabric defect detection is generally performed based on human visual inspection. This
method is not effective and it has various difficulties such as eye delusion and labor cost. To …

基于卷积神经网络的织物图像识别技术具有自主学习, 准确率高和适用性广的优点,
已被广泛应用于纺织工业生产中. 本文面向纺织领域详细综述了基于卷积神经网络的疵点分类 …