Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks
T Schlosser, M Friedrich, F Beuth… - Journal of Intelligent …, 2022 - Springer
In the semiconductor industry, automated visual inspection aims to improve the detection
and recognition of manufacturing defects by leveraging the power of artificial intelligence …
and recognition of manufacturing defects by leveraging the power of artificial intelligence …
A novel visual fault detection and classification system for semiconductor manufacturing using stacked hybrid convolutional neural networks
T Schlosser, F Beuth, M Friedrich… - 2019 24th IEEE …, 2019 - ieeexplore.ieee.org
Automated visual inspection in the semiconductor industry aims to detect and classify
manufacturing defects utilizing modern image processing techniques. While an earliest …
manufacturing defects utilizing modern image processing techniques. While an earliest …
Design of deep convolutional neural network architectures for automated feature extraction in industrial inspection
D Weimer, B Scholz-Reiter, M Shpitalni - CIRP annals, 2016 - Elsevier
Fast and reliable industrial inspection is a main challenge in manufacturing scenarios.
However, the defect detection performance is heavily dependent on manually defined …
However, the defect detection performance is heavily dependent on manually defined …
A fast and robust convolutional neural network-based defect detection model in product quality control
The fast and robust automated quality visual inspection has received increasing attention in
the product quality control for production efficiency. To effectively detect defects in products …
the product quality control for production efficiency. To effectively detect defects in products …
Deep CNN-based visual defect detection: Survey of current literature
SB Jha, RF Babiceanu - Computers in Industry, 2023 - Elsevier
In the past years, the computer vision domain has been profoundly changed by the advent of
deep learning algorithms and data science. The defect detection problem is of outmost …
deep learning algorithms and data science. The defect detection problem is of outmost …
Defect classification and detection using a multitask deep one-class CNN
Defect classification and detection have been explored using convolutional neural networks
(CNNs). Normally, a large set of training images containing defects and the associated …
(CNNs). Normally, a large set of training images containing defects and the associated …
State of the art in defect detection based on machine vision
Z Ren, F Fang, N Yan, Y Wu - International Journal of Precision …, 2022 - Springer
Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect
detection. In visual inspection, excellent optical illumination platforms and suitable image …
detection. In visual inspection, excellent optical illumination platforms and suitable image …
Deep learning for automatic vision-based recognition of industrial surface defects: a survey
Automatic vision-based inspection systems have played a key role in product quality
assessment for decades through the segmentation, detection, and classification of defects …
assessment for decades through the segmentation, detection, and classification of defects …
Using deep learning to detect defects in manufacturing: a comprehensive survey and current challenges
J Yang, S Li, Z Wang, H Dong, J Wang, S Tang - Materials, 2020 - mdpi.com
The detection of product defects is essential in quality control in manufacturing. This study
surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects …
surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects …
A weakly supervised surface defect detection based on convolutional neural network
L Xu, S Lv, Y Deng, X Li - IEEE Access, 2020 - ieeexplore.ieee.org
Surface defect detection is a critical task in product quality assurance for manufacturing
lines. The deep learning-based methods recently developed for defect detection are …
lines. The deep learning-based methods recently developed for defect detection are …