Why Manufacturing’s AI Divide Is Growing For Mid-Market Companies

Many smaller manufacturers assume they are already behind. But in truth, most of the industry is still early in the AI ...
IEEE

A computer vision-aided lightweight attention-augmented approach for nondestructive steel wire rope defect detection

Abstract: Steel wire rope (SWR), as critical load-bearing components in engineering, require precise and real-time nondestructive testing of surface defects to ensure industrial safety. However, in ...
GitHub

Surface Defect Detection: Dataset & Papers

At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery ...
elektormagazine

PCB Defect Detection: Computer Vision with Raspberry Pi

Machine learning enables real-time PCB defect detection using a FOMO model on a Raspberry Pi. Learn how this approach helps manufacturers catch errors early and reduce defects. In this article, we ...
IEEE

AI-Driven Computer Vision for Defect Detection

This research presents a deep learning-based automated product defect detection system to address limitations of conventional manual inspection techniques that are labor-intensive and prone to errors.
Scientific Research Publishing

Defect Detection in Manufacturing: An Integrated Deep Learning Approach ()

This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for classification and ...
GitHub

Defect detection using computer vision at the edge with Amazon SageMaker

This repository is related to our blog post Detect industrial defects at low latency with computer vision at the edge with Amazon SageMaker Edge in the AWS Machine Learning blog. In this workshop, we ...