| CPC H01L 21/67253 (2013.01) [G06N 3/045 (2023.01); G06T 7/0004 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30148 (2013.01)] | 12 Claims |
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1. A method for determining whether a substrate treatment process is normal using a deep learning model, the method comprising:
receiving an input image of a substrate processing;
preprocessing the input image;
choosing a recognized tip area of a nozzle as a region of interest (ROI);
learning the preprocessed input image by using a deep learning model; and
comparing a real time substrate treatment process image and a learned data by using the trained deep learning model to determine whether the substrate treatment process is normal,
wherein the preprocessing the input image comprises recognizing the tip area of a nozzle in the input image of the substrate processing, a chemical being sprayed from the tip area of the nozzle from which a chemical is to be sprayed,
wherein the learning the preprocessed input image by using the deep learning model comprises learning the ROI according to flow rates of the chemical.
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