发明授权
- 专利标题: Training spectrum generation for machine learning system for spectrographic monitoring
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申请号: US16449183申请日: 2019-06-21
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公开(公告)号: US11507824B2公开(公告)日: 2022-11-22
- 发明人: Benjamin Cherian , Nicholas Wiswell , Jun Qian , Thomas H. Osterheld
- 申请人: Applied Materials, Inc.
- 申请人地址: US CA Santa Clara
- 专利权人: Applied Materials, Inc.
- 当前专利权人: Applied Materials, Inc.
- 当前专利权人地址: US CA Santa Clara
- 代理机构: Fish & Richardson P.C.
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G05B13/02 ; G05B19/4063 ; G05B19/4155 ; G06N3/04 ; H01L21/66
摘要:
A method of generating training spectra for training of a neural network includes generating a plurality of theoretically generated initial spectra from an optical model, sending the plurality of theoretically generated initial spectra to a feedforward neural network to generate a plurality of modified theoretically generated spectra, sending an output of the feedforward neural network and empirically collected spectra to a discriminatory convolutional neural network, determining that the discriminatory convolutional neural network does not discriminate between the modified theoretically generated spectra and empirically collected spectra, and thereafter, generating a plurality of training spectra from the feedforward neural network.
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