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 of recent advances in surface defect detection using texture analysis techniques
X **e - ELCVIA: electronic letters on computer vision and …, 2008 - raco.cat
In this paper, we systematically review recent advances in surface inspection using
computer vision and image processing techniques, particularly those based on texture …
computer vision and image processing techniques, particularly those based on texture …
PGA-Net: Pyramid feature fusion and global context attention network for automated surface defect detection
Surface defect detection is a critical task in industrial production process. Nowadays, there
are lots of detection methods based on computer vision and have been successfully applied …
are lots of detection methods based on computer vision and have been successfully applied …
A generic deep-learning-based approach for automated surface inspection
Automated surface inspection (ASI) is a challenging task in industry, as collecting training
dataset is usually costly and related methods are highly dataset-dependent. In this paper, a …
dataset is usually costly and related methods are highly dataset-dependent. In this paper, a …
From BoW to CNN: Two decades of texture representation for texture classification
Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …
is one of the essential and challenging problems in computer vision and pattern recognition …
Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning
Quality control is a fundamental component of many manufacturing processes, especially
those involving casting or welding. However, manual quality control procedures are often …
those involving casting or welding. However, manual quality control procedures are often …
An unsupervised-learning-based approach for automated defect inspection on textured surfaces
S Mei, H Yang, Z Yin - IEEE transactions on instrumentation …, 2018 - ieeexplore.ieee.org
Automated defect inspection has long been a challenging task especially in industrial
applications, where collecting and labeling large amounts of defective samples are usually …
applications, where collecting and labeling large amounts of defective samples are usually …
Unsupervised anomaly segmentation via deep feature reconstruction
Automatic detecting anomalous regions in images of objects or textures without priors of the
anomalies is challenging, especially when the anomalies appear in very small areas of the …
anomalies is challenging, especially when the anomalies appear in very small areas of the …
Hyperspectral image classification with context-aware dynamic graph convolutional network
In hyperspectral image (HSI) classification, spatial context has demonstrated its significance
in achieving promising performance. However, conventional spatial context-based methods …
in achieving promising performance. However, conventional spatial context-based methods …
Multiscale feature-clustering-based fully convolutional autoencoder for fast accurate visual inspection of texture surface defects
Visual inspection of texture surface defects is still a challenging task in the industrial
automation field due to the tremendous changes in the appearance of various surface …
automation field due to the tremendous changes in the appearance of various surface …