Weakly Supervised Image Segmentation for Detecting Defects From Scanning Electron Microscopy Images in Semiconductor

Weakly Supervised Image Segmentation for Detecting Defects From Scanning Electron Microscopy Images in Semiconductor

The continuous miniaturization of semiconductor patterns improves performance but also leads to frequent pattern disruptions that significantly reduce manufacturing yields. In the field, scanning electron microscope (SEM) images of defects are analyzed to gain insight for improvement. However, manua...

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Bibliographic Details
Main Authors: Younghwan Lee, Seoung Bum Kim
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Cost-effective training data
high-quality pseudo label
semantic segmentation
semiconductor defect SEM image
weakly supervised learning
Online Access:https://ieeexplore.ieee.org/document/10786013/

Internet

https://ieeexplore.ieee.org/document/10786013/

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