Automatic Classification of Defect Pattern on Wafer-An application of Support Vector Machine
碩士 === 國立虎尾科技大學 === 資訊管理研究所在職專班 === 99 === In the particle inspection process of semiconductor industrial, inspectors always require much time to review the pattern of the defect by their eyes. They can further discover the abnormal situations and the reasons, which can be eliminated to decrease...
Main Authors: | Yi-Hsiang Chen, 陳詣享 |
---|---|
Other Authors: | 胡念祖 |
Format: | Others |
Language: | zh-TW |
Published: |
2011
|
Online Access: | http://ndltd.ncl.edu.tw/handle/86ey35 |
Similar Items
-
Automatic Classification and Correlation Analysis of Wafer Defect Patterns
by: Cho-Ming Tu, et al.
Published: (2008) -
Applying Support Vector Machine for Wafer Bin Map Classification
by: 黃安橦
Published: (2005) -
Automatic Task Classification via Support Vector Machine and Crowdsourcing
by: Hyungsik Shin, et al.
Published: (2018-01-01) -
A neural-network approach for wafer defects pattern classification
by: Ching-Ming Wu, et al.
Published: (2005) -
Automated Detection and Classification of Defective and Abnormal Dies in Wafer Images
by: Hsiang-Chieh Chen
Published: (2020-05-01)