- 专利标题: System using film thickness estimation from machine learning based processing of substrate images
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申请号: US17359345申请日: 2021-06-25
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公开(公告)号: US11847776B2公开(公告)日: 2023-12-19
- 发明人: Sivakumar Dhandapani , Arash Alahgholipouromrani , Dominic J. Benvegnu , Jun Qian , Kiran Lall Shrestha
- 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: G06T7/00
- IPC分类号: G06T7/00 ; G06T7/60 ; B24B37/013
摘要:
A neural network is trained for use in a substrate thickness measurement system by obtaining ground truth thickness measurements of a top layer of a calibration substrate at a plurality of locations, each location at a defined position for a die being fabricated on the substrate. A plurality of color images of the calibration substrate are obtained, each color image corresponding to a region for a die being fabricated on the substrate. A neural network is trained to convert color images of die regions from an in-line substrate imager to thickness measurements for the top layer in the die region. The training is performed using training data that includes the plurality of color images and ground truth thickness measurements with each respective color image paired with a ground truth thickness measurement for the die region associated with the respective color image.
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