Presentation | 2006-03-16 Recognition Method of Minute Defect Based on Statistical Outlier Detection using Plural Pattern Images Kaoru SAKAI, Shunji MAEDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Reductions of the pattern variation noise caused by the manufacturing process are essential to recognize a minute defect on the complicated multilayer patterns of semiconductor wafers. We propose a highly sensitive comparison inspection method with noise reduction. We control the scattergram data of images by using plural images and we recognize the minute defect as an outlier. This new method can detect small defects that exceed the resolution limit in optics. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Comparison inspection / Defect recognition / Statistical outlier detection |
Paper # | PRMU2005-233 |
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Committee | PRMU |
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Conference Date | 2006/3/9(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Recognition Method of Minute Defect Based on Statistical Outlier Detection using Plural Pattern Images |
Sub Title (in English) | |
Keyword(1) | Comparison inspection |
Keyword(2) | Defect recognition |
Keyword(3) | Statistical outlier detection |
1st Author's Name | Kaoru SAKAI |
1st Author's Affiliation | Hitachi,LTD., Production Engineering Research Laboratory() |
2nd Author's Name | Shunji MAEDA |
2nd Author's Affiliation | Hitachi,LTD., Production Engineering Research Laboratory |
Date | 2006-03-16 |
Paper # | PRMU2005-233 |
Volume (vol) | vol.105 |
Number (no) | 673 |
Page | pp.pp.- |
#Pages | 6 |
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