- Patent Title: Wafer map pattern detection based on supervised machine learning
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Application No.: US15966375Application Date: 2018-04-30
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Publication No.: US10657638B2Publication Date: 2020-05-19
- Inventor: Patrick Jon Milligan
- Applicant: Mentor Graphics Corporation
- Applicant Address: US OR Wilsonville
- Assignee: Mentor Graphics Corporation
- Current Assignee: Mentor Graphics Corporation
- Current Assignee Address: US OR Wilsonville
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; G06N3/04 ; G06K9/66 ; G06N20/00 ; G06N3/08 ; G06N3/12 ; G06N20/10

Abstract:
Various aspects of the disclosed technology relate to training and applying a machine learning model for defect pattern detection. Defect pattern variants of one or more defect patterns are generated. The one or more defect patterns are extracted from wafer maps of wafers having at least systematic defects. Each of the generated defect pattern variants is superimposed on wafer maps of wafers having no systematic defects to generate positive training data of wafer maps, which are included in a training dataset. Based on the training dataset, a trained machine-learning model for recognizing known defect patterns on wafer maps is derived.
Public/Granted literature
- US20180330493A1 Wafer Map Pattern Detection Based On Supervised Machine Learning Public/Granted day:2018-11-15
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