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:
Oct. 19, 2021

Filed:

Feb. 15, 2019
Applicant:

Kla-tencor Corporation, Milpitas, CA (US);

Inventors:

Santosh Bhattacharyya, Milpitas, CA (US);

Jacob George, Milpitas, CA (US);

Saravanan Paramasivam, Chennai, IN;

Martin Plihal, Pleasanton, CA (US);

Assignee:

KLA Corporation, Milpitas, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06K 9/62 (2006.01); G01N 23/2251 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0004 (2013.01); G01N 23/2251 (2013.01); G06K 9/6253 (2013.01); G06K 9/6256 (2013.01); G06K 9/6262 (2013.01); G06K 9/6267 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G01N 2223/646 (2013.01); G06T 2207/10061 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

A system for defect review and classification is disclosed. The system may include a controller, wherein the controller may be configured to receive one or more training images of a specimen. The one or more training images including a plurality of training defects. The controller may be further configured to apply a plurality of difference filters to the one or more training images, and receive a signal indicative of a classification of a difference filter effectiveness metric for at least a portion of the plurality of difference filters. The controller may be further configured to generate a deep learning network classifier based on the received classification and the attributes of the plurality of training defects. The controller may be further configured to extract convolution layer filters of the deep learning network classifier, and generate one or more difference filter recipes based on the extracted convolution layer filters.


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