Nature

An improved steel defect detection model using multi-scale feature fusion based on YOLO-MFD

To address the challenges of limited detection accuracy for small targets in complex backgrounds and the difficulty in model deployment due to a large number of parameters in steel surface defect ...
Nature

Optimization of deep learning-based faster R-CNN network for vehicle detection

Object detection is a critical task in computer vision, involving the identification and localization of objects within an image 1. Object detection algorithms typically extract meaningful results ...

'Flawless on the outside, flipped within': Detecting hidden defects in 2D dielectrics with light

A material may appear flawless on the surface yet fail to function properly. The cause lies in structural defects hidden ...
pv magazine International

Detecting PV module defects at a single glance

Researchers in China have developed a novel deep learning model to detect defects in photovoltaic panels. The approach leverages high-resolution visible light imaging to identify defects using an ...
Semiconductor Engineering

Refining Vision-Language Models For Lithography Defect Detection

“Semiconductor lithography inspection requires reliable detection of small pattern defects such as bridge, burr, pinch, and contamination. In this study, we propose a two-stage vision-language ...
Semiconductor Engineering

AI Models Transform Defect Inspection And Review, But Can Fail To Scale

AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.