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 …
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 …
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 …
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 …
Automated defect inspection system for metal surfaces based on deep learning and data augmentation
Recent efforts to create a smart factory have inspired research that analyzes process data
collected from Internet of Things (IOT) sensors, to predict product quality in real time. This …
collected from Internet of Things (IOT) sensors, to predict product quality in real time. This …
Automatic metallic surface defect detection and recognition with convolutional neural networks
X Tao, D Zhang, W Ma, X Liu, D Xu - Applied Sciences, 2018 - mdpi.com
Automatic metallic surface defect inspection has received increased attention in relation to
the quality control of industrial products. Metallic defect detection is usually performed …
the quality control of industrial products. Metallic defect detection is usually performed …
[HTML][HTML] Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning
MK Ferguson, AK Ronay, YTT Lee… - Smart and sustainable …, 2018 - ncbi.nlm.nih.gov
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 …
A deep learning-based surface defect inspection system using multiscale and channel-compressed features
In machine vision-based surface inspection tasks, defects are typically considered as local
anomalies in homogeneous background. However, industrial workpieces commonly contain …
anomalies in homogeneous background. However, industrial workpieces commonly contain …
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 …
Fully convolutional networks for surface defect inspection in industrial environment
In this paper, we propose a reusable and high-efficiency two-stage deep learning based
method for surface defect inspection in industrial environment. Aiming to achieve trade-offs …
method for surface defect inspection in industrial environment. Aiming to achieve trade-offs …