Surface defect classification of steels with a new semi-supervised learning method
H Di, X Ke, Z Peng, Z Dongdong - Optics and Lasers in Engineering, 2019 - Elsevier
Defect inspection is extremely crucial to ensure the quality of steel surface. It affects not only
the subsequent production, but also the quality of the end-products. However, due to the …
the subsequent production, but also the quality of the end-products. However, due to the …
Semi-supervised defect classification of steel surface based on multi-training and generative adversarial network
Defect inspection is very important for guaranteeing the surface quality of industrial steel
products, but related methods are based primarily on supervised learning which requires …
products, but related methods are based primarily on supervised learning which requires …
A semi-supervised convolutional neural network-based method for steel surface defect recognition
Y Gao, L Gao, X Li, X Yan - Robotics and Computer-Integrated …, 2020 - Elsevier
Automatic defect recognition is one of the research hotspots in steel production, but most of
the current methods focus on supervised learning, which relies on large-scale labeled …
the current methods focus on supervised learning, which relies on large-scale labeled …
TLU-net: a deep learning approach for automatic steel surface defect detection
Visual steel surface defect detection is an essential step in steel sheet manufacturing.
Several machine learning-based automated visual inspection (AVI) methods have been …
Several machine learning-based automated visual inspection (AVI) methods have been …
Unveiling patterns: A study on semi-supervised classification of strip surface defects
Y Liu, H Yang, C Wu - IEEE Access, 2023 - ieeexplore.ieee.org
As a critical intermediate material in the iron and steel industry, strip steel will inevitably have
various surface defects during its processing, which directly affects the service performance …
various surface defects during its processing, which directly affects the service performance …
A hierarchical training-convolutional neural network with feature alignment for steel surface defect recognition
Steel is a basic material, and vision-based defect recognition is important for quality.
Recently, deep learning, especially convolutional neural network (CNN), has become a …
Recently, deep learning, especially convolutional neural network (CNN), has become a …
Automatic detection and classification of steel surface defect using deep convolutional neural networks
S Wang, X Xia, L Ye, B Yang - Metals, 2021 - mdpi.com
Automatic detection of steel surface defects is very important for product quality control in the
steel industry. However, the traditional method cannot be well applied in the production line …
steel industry. However, the traditional method cannot be well applied in the production line …
Steel surface defect recognition: A survey
Steel surface defect recognition is an important part of industrial product surface defect
detection, which has attracted more and more attention in recent years. In the development …
detection, which has attracted more and more attention in recent years. In the development …
A deep-learning-based approach for fast and robust steel surface defects classification
Automatic visual recognition of steel surface defects provides critical functionality to facilitate
quality control of steel strip production. In this paper, we present a compact yet effective …
quality control of steel strip production. In this paper, we present a compact yet effective …
A steel surface defect recognition algorithm based on improved deep learning network model using feature visualization and quality evaluation
S Guan, M Lei, H Lu - IEEE Access, 2020 - ieeexplore.ieee.org
Steel defect detection is used to detect defects on the surface of the steel and to improve the
quality of the steel surface. However, traditional image detection algorithms cannot meet the …
quality of the steel surface. However, traditional image detection algorithms cannot meet the …