Deep Learning Networks for Nuisance Filtering

    公开(公告)号:US20210125325A1

    公开(公告)日:2021-04-29

    申请号:US16663283

    申请日:2019-10-24

    Abstract: Methods and systems for detecting defects on a specimen are provided. One system includes a first deep learning (DL) network configured for filtering nuisances from defect candidates detected on a specimen. Output of the first DL network includes a first subset of the defect candidates not filtered as the nuisances. The system also includes a second DL network configured for filtering nuisances from the first subset of the defect candidates. Computer subsystem(s) input high resolution images acquired for the first subset of the defect candidates into the second DL network. Output of the second DL network includes a final subset of the defect candidates not filtered as the nuisances. The computer subsystem(s) designate the defect candidates in the final subset as defects on the specimen and generate results for the defects.

    Deep learning networks for nuisance filtering

    公开(公告)号:US11087449B2

    公开(公告)日:2021-08-10

    申请号:US16663283

    申请日:2019-10-24

    Abstract: Methods and systems for detecting defects on a specimen are provided. One system includes a first deep learning (DL) network configured for filtering nuisances from defect candidates detected on a specimen. Output of the first DL network includes a first subset of the defect candidates not filtered as the nuisances. The system also includes a second DL network configured for filtering nuisances from the first subset of the defect candidates. Computer subsystem(s) input high resolution images acquired for the first subset of the defect candidates into the second DL network. Output of the second DL network includes a final subset of the defect candidates not filtered as the nuisances. The computer subsystem(s) designate the defect candidates in the final subset as defects on the specimen and generate results for the defects.

    Alignment of a Specimen for Inspection and Other Processes

    公开(公告)号:US20220101506A1

    公开(公告)日:2022-03-31

    申请号:US17157992

    申请日:2021-01-25

    Abstract: Methods and systems for setting up alignment of a specimen are provided. One system includes computer subsystem(s) configured for acquiring two-dimensional (2D) images generated from output of a detector of an output acquisition subsystem at template locations in corresponding areas of printed instances on a specimen. The computer subsystem(s) determine offsets in x and y directions between the template locations using the 2D images and determine an angle of the specimen with respect to the output acquisition subsystem based on the offsets. If the angle is greater than a predetermined value, the computer subsystem(s) rotate the specimen and repeat the steps described above. If the angle is less than the predetermined value, the computer subsystem(s) store one of the 2D images for alignment of the specimen in a process performed on a specimen. The 2D images may include multi-mode images, which may be fused prior to determining the offsets.

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