- 专利标题: Training Spectrum Generation for Machine Learning System for Spectrographic Monitoring
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申请号: US18310520申请日: 2023-05-01
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公开(公告)号: US20230267329A1公开(公告)日: 2023-08-24
- 发明人: Benjamin Cherian , Nicholas A. 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
- 分案原申请号: US16449104 2019.06.21
- 主分类号: G06N3/08
- IPC分类号: G06N3/08 ; G05B19/4063 ; G05B19/4155 ; H01L21/66 ; G05B13/02 ; G06N3/045
摘要:
A method of generating training spectra for training of a neural network includes measuring a first plurality of training spectra from one or more sample substrates, measuring a characterizing value for each training spectra of the plurality of training spectra to generate a plurality of characterizing values with each training spectrum having an associated characterizing value, measuring a plurality of dummy spectra during processing of one or more dummy substrates, and generating a second plurality of training spectra by combining the first plurality of training spectra and the plurality of dummy spectra, there being a greater number of spectra in the second plurality of training spectra than in the first plurality of training spectra. Each training spectrum of the second plurality of training spectra having an associated characterizing value.
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