Invention Application
- Patent Title: METHOD OF DEEP LEARINING-BASED EXAMINATION OF A SEMICONDUCTOR SPECIMEN AND SYSTEM THEREOF
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Application No.: US15668623Application Date: 2017-08-03
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Publication No.: US20170357895A1Publication Date: 2017-12-14
- Inventor: Leonid KARLINSKY , Boaz COHEN , Idan KAIZERMAN , Efrat ROSENMAN , Amit BATIKOFF , Daniel RAVID , Moshe ROSENWEIG
- Applicant: Applied Materials Israel Ltd.
- Main IPC: G06N3/08
- IPC: G06N3/08

Abstract:
There are provided system and method of segmentation a fabrication process (FP) image obtained in a fabrication of a semiconductor specimen. The method comprises: upon obtaining a Deep Neural Network (DNN) trained to provide segmentation-related data, processing a fabrication process (FP) sample using the obtained trained DNN and, resulting from the processing, obtaining by the computer segments-related data characterizing the FP image to be segmented, the obtained segments-related data usable for automated examination of the semiconductor specimen. The DNN is trained using a segmentation training set comprising a plurality of first training samples and ground truth data associated therewith, each first training sample comprises a training image; FP sample comprises the FP image to be segmented.
Public/Granted literature
- US11010665B2 Method of deep learning-based examination of a semiconductor specimen and system thereof Public/Granted day:2021-05-18
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