Abstract: Automatic detection of textile defects is a crucial factor in improving textile quality. Fast and accurate detection of these defects is key to achieving automation in the textile industry.

Abstract: Automatic surface defect detection is a critical technique for ensuring product quality in industrial casting production. While general object detection techniques have made remarkable ...

What if manufacturing companies could pinpoint the exact cause of a defect the moment it occurs, preventing costly production delays and ensuring top-notch quality? Generative artificial intelligence ...

Effectively detecting subtle surface defects in strip steel is vital for industrial quality assurance; however, most existing approaches fail to strike an optimal balance between accuracy and ...

Two years after a panel flew off a 737 Max, Boeing is doing more inspections, completing work in its intended order and making other changes. Can the company keep it up? The number of 737 Max planes ...

Wood, a widely distributed renewable resource, plays a vital role in accelerating urbanisation. However, wood grain defects pose significant safety hazards. Detecting these defects is challenging due ...

New issue New issue Open Open [Ray Data]Pylint detection found some Python code defects in ray data #53881 ...

This repository contains the code and resources for a PCB defect detection project. The project uses YOLO and other comparative models to detect and classify PCB defects, along with improvements to ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...