Automated surface defect detection framework using machine vision and convolutional neural networks

SA Singh, KA Desai - Journal of Intelligent Manufacturing, 2023 - Springer
Abstract Machine vision-based inspection technologies are gaining considerable
importance for automated monitoring and quality control of manufactured products in recent …

Comparative assessment of common pre-trained CNNs for vision-based surface defect detection of machined components

SA Singh, AS Kumar, KA Desai - Expert Systems with Applications, 2023 - Elsevier
Abstract Small and Medium Enterprises (SMEs) and Micro, Small, and Medium Enterprises
(MSMEs) contemplate integrating machine vision with high throughput manufacturing lines …

A lightweight surface defect detection framework combined with dual-domain attention mechanism

J Tang, Z Wang, H Zhang, H Li, P Wu, N Zeng - Expert Systems with …, 2024 - Elsevier
In this paper, a lightweight printed circuit board (PCB) defects detection model (light-PDD) is
proposed, which mainly concentrates on overcoming the deficiencies of redundant …

[PDF][PDF] Surface Characteristics Measurement Using Computer Vision: A Review.

AW Hashmi, HS Mali, A Meena… - … in Engineering & …, 2023 - researchgate.net
Computer vision provides image-based solutions to inspect and investigate the quality of the
surface to be measured. For any components to execute their intended functions and …

An improved VGG19 transfer learning strip steel surface defect recognition deep neural network based on few samples and imbalanced datasets

X Wan, X Zhang, L Liu - Applied Sciences, 2021 - mdpi.com
The surface defects' region of strip steel is small, and has various defect types and, complex
gray structures. There tend to be a large number of false defects and edge light interference …

[PDF][PDF] Review of industry workpiece classification and defect detection using deep learning

C Chen, A Abdullah, SH Kok… - International Journal of …, 2022 - researchgate.net
Object detection and classification denotes one of the most extensively-utilized machine
vision applications given the high requirements put forward for object classification and …

Steel surface defect detection using an ensemble of deep residual neural networks

I Konovalenko, P Maruschak… - … of Computing and …, 2022 - asmedigitalcollection.asme.org
Steel defect diagnostics is important for industry task as it is tied to the product quality and
production efficiency. The aim of this paper is evaluating the application of residual neural …

Metal surface defect detection based on improved YOLOv5

C Zhou, Z Lu, Z Lv, M Meng, Y Tan, K Xia, K Liu… - Scientific Reports, 2023 - nature.com
During the production of metal material, various complex defects may come into being on
the surface, together with large amount of background texture information, causing false or …

HDR image-based deep learning approach for automatic detection of split defects on sheet metal stamping parts

AR Singh, T Bashford-Rogers, D Marnerides… - … International Journal of …, 2023 - Springer
Sheet metal stamping is widely used for high-volume production. Despite the wide adoption,
it can lead to defects in the manufactured components, making their quality unacceptable …

MA-YOLO: a method for detecting surface defects of aluminum profiles with attention guidance

L Jiang, B Yuan, Y Wang, Y Ma, J Du, F Wang… - IEEE …, 2023 - ieeexplore.ieee.org
Aluminum Profiles (APs) are aluminum materials obtained by hot melting and extruding
aluminum rods. It has the characteristics of low cost, strong plasticity, easy processing, and …