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    Using transformations to verify computer vision quality
    3.
    发明授权
    Using transformations to verify computer vision quality 有权

    公开(公告)号：US10902295B2

    公开(公告)日：2021-01-26

    申请号：US16270910

    申请日：2019-02-08

    Applicant: SAP SE

    Inventor： Juliy Broyda

    IPC: G06K9/62 ,  G06N20/00 ,  G06N3/08 ,  G06T3/40 ,  G06T3/60

    Abstract: Techniques for using image dataset transformations to verify the quality of a computer vision system are disclosed. In some example embodiments, a computer-implemented method comprises: accessing a database to obtain a reference image; generating a plurality of new images based on the reference image using a plurality of transformations, each one of the plurality of transformations being configured to change a corresponding visual property of the reference image; feeding the plurality of new images into an image classifier to generate a corresponding classification result for each one of the plurality of new images; determining that the image classifier does not satisfy one or more accuracy criteria based on the generated classification results for the plurality of new images; and based on the determining that the image classifier does not satisfy the one or more accuracy criteria, selectively performing a function.

    ANOMALY AND FRAUD DETECTION WITH FAKE EVENT DETECTION USING MACHINE LEARNING
    5.
    发明申请
    ANOMALY AND FRAUD DETECTION WITH FAKE EVENT DETECTION USING MACHINE LEARNING 有权

    公开(公告)号：US20210004580A1

    公开(公告)日：2021-01-07

    申请号：US16711642

    申请日：2019-12-12

    Applicant: SAP SE

    Inventor： Suchitra Sundararaman ,  Jesper Lind ,  Juliy Broyda ,  Lev Sigal ,  Anton Ioffe ,  Yuri Arshavski

    IPC: G06K9/00 ,  G06N20/00 ,  G06K9/62 ,  G06N3/02

    Abstract: The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes training at least one machine learning model to determine features that can be used to determine whether an image is an authentic image of a document or an automatically generated document image, using a training set of authentic images and a training set of automatically generated document images. A request to classify an image as either an authentic image of a document or an automatically generated document image is received. The machine learning model(s) are used to classify the image as either an authentic image of a document or an automatically generated document image, based on features included in the image that are identified by the machine learning model(s). A classification of the image is provided. The machine learning model(s) are updated based on the image and the classification of the image.

    ANOMALY AND FRAUD DETECTION WITH FAKE EVENT DETECTION USING LINE ORIENTATION TESTING
    7.
    发明申请
    ANOMALY AND FRAUD DETECTION WITH FAKE EVENT DETECTION USING LINE ORIENTATION TESTING 有权

    公开(公告)号：US20210004949A1

    公开(公告)日：2021-01-07

    申请号：US16711698

    申请日：2019-12-12

    Applicant: SAP SE

    Inventor： Juliy Broyda ,  Lev Sigal ,  Anton Ioffe ,  Yuri Arshavski

    IPC: G06T7/00 ,  G06Q40/00 ,  G06N3/08 ,  G06K9/00 ,  G06T7/73

    Abstract: The present disclosure involves systems, software, and computer implemented methods for transaction auditing. One example method includes receiving a request to authenticate a document image. The image is preprocessed to prepare the image for line orientation analysis. The preprocessed image is analyzed to determine lines in the preprocessed image. The determined lines are automatically analyzed by performing line orientation test(s) on the determined lines to generate line orientation test result(s) for the preprocessed image. The line orientation test result(s) are evaluated to determine whether the image is authentic. In response to determining that at least one line orientation test result matches a predefined condition corresponding to an unauthentic document, a determination is made that the image is not authentic. In response to determining that none of the line orientation test results match any predefined condition corresponding to an unauthentic document, a determination is made that the image is authentic.

    USING TRANSFORMATIONS TO VERIFY COMPUTER VISION QUALITY
    8.
    发明申请
    USING TRANSFORMATIONS TO VERIFY COMPUTER VISION QUALITY 审中-公开

    公开(公告)号：US20200257941A1

    公开(公告)日：2020-08-13

    申请号：US16270910

    申请日：2019-02-08

    Applicant: SAP SE

    Inventor： Juliy Broyda

    IPC: G06K9/62 ,  G06T3/60 ,  G06T3/40 ,  G06N3/08 ,  G06N20/00

    Abstract: Techniques for using image dataset transformations to verify the quality of a computer vision system are disclosed. In some example embodiments, a computer-implemented method comprises: accessing a database to obtain a reference image; generating a plurality of new images based on the reference image using a plurality of transformations, each one of the plurality of transformations being configured to change a corresponding visual property of the reference image; feeding the plurality of new images into an image classifier to generate a corresponding classification result for each one of the plurality of new images; determining that the image classifier does not satisfy one or more accuracy criteria based on the generated classification results for the plurality of new images; and based on the determining that the image classifier does not satisfy the one or more accuracy criteria, selectively performing a function.

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