Invention Grant
- Patent Title: Generating synthetic layout patterns by feedforward neural network based variational autoencoders
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Application No.: US15994461Application Date: 2018-05-31
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Publication No.: US10592635B2Publication Date: 2020-03-17
- Inventor: Jing Sha , Michael A. Guillorn , Derren N. Dunn
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Vazken Alexanian
- Main IPC: G06F17/50
- IPC: G06F17/50 ; G06N3/04 ; G06N5/04 ; G06N3/08

Abstract:
A computer-implemented method, computer program product, and computer processing system are provided for generating synthetic layout patterns. The method includes receiving, by a processor, a set of physical design layouts that include a variety of layout patterns for neural network training. The method further includes generating, by the processor, a set of training layout pattern images for the neural network training by performing automatic image capturing on the set of physical design layouts with scripts. The method also includes training, by the processor, a feedforward neural network (FFNN)-based Variational Autoencoder (VAE) with the set of training layout pattern images. The method additionally includes generating, by the processor using the FFNN-based VAE, new synthetic layout images.
Public/Granted literature
- US20190370435A1 GENERATING SYNTHETIC LAYOUT PATTERNS BY FEEDFORWARD NEURAL NETWORK BASED VARIATIONAL AUTOENCODERS Public/Granted day:2019-12-05
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