Fabric defects detection plays a critical role in the quality control of textile manufacturing
industry. It is still a challenge to realize accurate fabric defects detection due to variations of …

On a global scale, the process of automatic defect detection represents a critical stage of
quality control in textile industries. In this paper, a semantic segmentation network using a …

First-article inspection of flexographic printing labels (FPLs) is significant before the mass
production of FPLs, which is manually implemented by quality check (QC) workers in real …

This paper introduces an unsupervised method for detecting regions with a high density of
nanomaterials on coated fabric using Variational Autoencoder, a generative model capable …

Detection of defects is an essential quality control method in fabric production. Unsupervised
deep learning‐based reconstruction algorithms have recently been deeply concerned owing …

Image retrieval is the process of searching and retrieving images from a datastore based on
their visual content and features. Recently, much attention has been directed towards the …

For sample reproduction, texture and color are both significant when the consumer has no
specific or individual demands or cannot describe the requirements clearly. In this paper, an …

为了解决柔印首件检验没有基准织物图像作为参照的难点, 该文提出一种以电子样稿为参照物的
柔印首件“粗-精” 检测方法, 主要分为粗匹配, 精匹配和缺陷检测3 个阶段. 首先 …

Content based image retrieval (CBIR) refers to a form of lookup that is performed on a set of
images. It is an attempt to find images from a dataset that are similar to a given input image …

In order to solve the problem that there is no real reference of the fabric image in the flexo
first item inspection, a coarse-to-fine inspection method of flexo first item is proposed based …