Recognition of semiconductor defect patterns using spatial filtering and spectral clustering-Reference-Cited by-同舟云学术

Recognition of semiconductor defect patterns using spatial filtering and spectral clustering

Published:2008-04 Issue:3 Volume:34 Page:1914-1923
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wang Chih-Hsuan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference34 articles.

1. Learning spectral clustering;Bach,2004

2. Bengio, Y., Vincent, P., & Paiement, J. F. (2003). Learning eigenfunctions of similarity: linking spectral clustering and kernel PCA. Technical Report, University de Montral.

3. Regularized Gaussian discriminant analysis through eigenvalue decomposition;Bensmail;Journal of the American Statistical Association,1996

4. Pattern recognition with fuzzy function algorithms;Bezdek,1981

5. A neural-network approach to recognize defect spatial pattern in semiconductor fabrication;Chen;IEEE Transactions on Semiconductor Manufacturing,2000

Cited by 63 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Implementation of Silicon Wafer Defect Classification Web application using Deep Learning;2024 International Conference on Advancements in Power, Communication and Intelligent Systems (APCI);2024-06-21

2. Prognostics for Semiconductor Sustainability: Tool Failure Behavior Prediction in Fabrication Processes;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-06

3. Development of a spatial dimension-based taxonomy for classifying the defect patterns in a wafer bin map;Advanced Engineering Informatics;2024-04

4. An efficient deep learning framework for mixed-type wafer map defect pattern recognition;AIP Advances;2024-04-01

5. An Elegantly Simple Approach for Wafer Feature Extraction and Defect Pattern Recognition;2023 International Semiconductor Conference (CAS);2023-10-11