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:
May. 12, 2020

Filed:

Dec. 01, 2015
Applicant:

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

Inventors:

Wei Chang, Foster City, CA (US);

Ramon Olavarria, Fremont, CA (US);

Krishna Rao, San Ramon, CA (US);

Assignee:

KLA-Tencor Corporation, Milpitas, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/46 (2006.01); G06K 9/62 (2006.01); G06K 9/66 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0004 (2013.01); G06K 9/4628 (2013.01); G06K 9/6255 (2013.01); G06K 9/6274 (2013.01); G06K 9/66 (2013.01); G06K 2209/19 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30148 (2013.01);
Abstract

Systems and methods for defection classification in a semiconductor process are provided. The system includes a communication line configured to receive a defect image of a wafer from the semiconductor process and a deep-architecture neural network in electronic communication with the communication line. The neural network has a first convolution layer of neurons configured to convolve pixels from the defect image with a filter to generate a first feature map. The neural network also includes a first subsampling layer configured to reduce the size and variation of the first feature map. A classifier is provided for determining a defect classification based on the feature map. The system may include more than one convolution layers and/or subsampling layers. A method includes extracting one or more features from a defect image using a deep-architecture neural network, for example a convolutional neural network.


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