ACTIVE LEARNING-BASED DEFECT LOCATION IDENTIFICATION

    公开(公告)号:US20230401694A1

    公开(公告)日:2023-12-14

    申请号:US18033786

    申请日:2021-11-02

    CPC classification number: G06T7/001 G06T2207/20081 G06T2207/30148

    Abstract: A method and apparatus for identifying locations to be inspected on a substrate is disclosed. A defect location prediction model is trained using a training dataset associated with other substrates to generate a prediction of defect or non-defect and a confidence score associated with the prediction for each of the locations based on process-related data associated with the substrates. Those of the locations determined by the defect location prediction model as having confidences scores satisfying a confidence threshold are added to a set of locations to be inspected by an inspection system. After the set of locations are inspected, the inspection results data is obtained, and the defect location prediction model is incrementally trained by using the inspection results data and process-related data for the set of locations as training data.

Patent Agency Ranking