The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 15, 2008

Filed:

Nov. 13, 2003
Applicants:

Lisheng Gao, Morgan Hill, CA (US);

BO Magluyan, Los Gatos, CA (US);

Jianxin Zhang, Santa Clara, CA (US);

Kevin Yeung, Sunnyvale, CA (US);

Kenong Wu, Davis, CA (US);

Tong Huang, San Jose, CA (US);

Inventors:

Lisheng Gao, Morgan Hill, CA (US);

Bo Magluyan, Los Gatos, CA (US);

Jianxin Zhang, Santa Clara, CA (US);

Kevin Yeung, Sunnyvale, CA (US);

Kenong Wu, Davis, CA (US);

Tong Huang, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
Abstract

Disclosed are methods and apparatus for efficiently setting up and maintaining a defect classification system. In general terms, the setup procedure optionally includes automatically grouping a set of provided defects and presenting a representative set from each defect group to the user for classification. After the initial manual classification of the representative defects, the setup procedure includes an automatic procedure for classifying the non-reviewed or unclassified defects based on the manual class codes from the user-reviewed defects. After the automatic classification operation, the user may also be presented with defects from each class which may require re-classification. In particular embodiments, the user is iteratively presented with defects which have classifications that are suspect, which are near classification boundaries, or have classifications that have a low confidence level until each class is pure or contains a same type of defect classes as assigned by the user.


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