Defect size measurement using deep learning methods
Abstract:
A system has detectors configured to receive a beam of light reflected from a wafer. For example, three detectors may be used. Each of the detectors is a different channel. Images from the detectors are combined into a pseudo-color RGB image. A convolutional neural network unit (CNN) can receive the pseudo-color RGB image and determine a size of a defect in the pseudo-color RGB image. The CNN also can classify the defect into a size category.
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