Visual-based defect detection and classification approaches for industrial applications—a survey
This paper reviews automated visual-based defect detection approaches applicable to
various materials, such as metals, ceramics and textiles. In the first part of the paper, we …
various materials, such as metals, ceramics and textiles. In the first part of the paper, we …
A review on recent advances in vision-based defect recognition towards industrial intelligence
In modern manufacturing, vision-based defect recognition is an essential technology to
guarantee product quality, and it plays an important role in industrial intelligence. With the …
guarantee product quality, and it plays an important role in industrial intelligence. With the …
Automatic fabric defect detection based on an improved YOLOv5
R **, Q Niu - Mathematical Problems in Engineering, 2021 - Wiley Online Library
Fabric defect detection is particularly remarkable because of the large textile production
demand in China. Traditional manual detection method is inefficient, time‐consuming …
demand in China. Traditional manual detection method is inefficient, time‐consuming …
Surface defect detection via entity sparsity pursuit with intrinsic priors
Computer vision based methods have been widely used in surface defect inspection.
However, most of these approaches are task specific, and it is hard to transfer them to similar …
However, most of these approaches are task specific, and it is hard to transfer them to similar …
A compact convolutional neural network for surface defect inspection
The advent of convolutional neural networks (CNNs) has accelerated the progress of
computer vision from many aspects. However, the majority of the existing CNNs heavily rely …
computer vision from many aspects. However, the majority of the existing CNNs heavily rely …
DMWMNet: A novel dual-branch multi-level convolutional network for high-performance mixed-type wafer map defect detection in semiconductor manufacturing
X Zhang, Z Jiang, H Yang, Y Mo, L Zhou, Y Zhang… - Computers in …, 2024 - Elsevier
Wafer map defect detection plays an important role in semiconductor manufacturing by
identifying root causes and accelerating process adjustments to ensure product quality and …
identifying root causes and accelerating process adjustments to ensure product quality and …
An edge-located uniform pattern recovery mechanism using statistical feature-based optimal center pixel selection strategy for local binary pattern
S Lan, H Fan, S Hu, X Ren, X Liao, Z Pan - Expert Systems with …, 2023 - Elsevier
Abstract The Local Binary Pattern (LBP) is a commonly used method for texture classification
that performs well in terms of feature discrimination. However,(1) LBP can misclassify some …
that performs well in terms of feature discrimination. However,(1) LBP can misclassify some …
A new method using the convolutional neural network with compressive sensing for fabric defect classification based on small sample sizes
The convolutional neural network (CNN) has recently achieved great breakthroughs in many
computer vision tasks. However, its application in fabric texture defects classification has not …
computer vision tasks. However, its application in fabric texture defects classification has not …
Edge-glued wooden panel defect detection using deep learning
The wood-based furniture manufacturing industries prioritize quality of production to meet
higher market demands. Identifying various types of edge-glued wooden panel defects are a …
higher market demands. Identifying various types of edge-glued wooden panel defects are a …
Surface defects detection using non-convex total variation regularized RPCA with kernelization
J Wang, G Xu, C Li, Z Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Surface defects have an adverse effect on the quality of industrial products, and vision-
based defect detection is widely researched due to its objective and stable performance …
based defect detection is widely researched due to its objective and stable performance …