Invention Grant
- Patent Title: Residue measurement from machine learning based processing of substrate images
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Application No.: US18496303Application Date: 2023-10-27
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Publication No.: US12272047B2Publication Date: 2025-04-08
- Inventor: Sivakumar Dhandapani , Arash Alahgholipouromrani , Dominic J. Benvegnu , Jun Qian , Kiran Lall Shrestha
- Applicant: Applied Materials, Inc
- Applicant Address: US CA Santa Clara
- Assignee: Applied Materials, Inc
- Current Assignee: Applied Materials, Inc
- Current Assignee Address: US CA Santa Clara
- Agency: Fish & Richardson P.C.
- Main IPC: G06T7/00
- IPC: G06T7/00 ; B24B37/013 ; G06T7/60

Abstract:
A neural network is trained for use in a substrate residue classification system by obtaining ground truth residue level 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 residue level measurements for the top layer in the die region.
Public/Granted literature
- US20240054634A1 RESIDUE CLASSIFICATION FROM MACHINE LEARNING BASED PROCESSING OF SUBSTRATE IMAGES Public/Granted day:2024-02-15
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