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    System for generating enhanced training data
    21.
    发明授权
    System for generating enhanced training data 有权

    公开(公告)号：US12190566B1

    公开(公告)日：2025-01-07

    申请号：US17652828

    申请日：2022-02-28

    Applicant: AMAZON TECHNOLOGIES, INC.

    Inventor： Lavisha Aggarwal ,  Manoj Aggarwal ,  Gerard Guy Medioni ,  Dilip Kumar

    IPC: G06V10/24 ,  G06V10/77 ,  G06V10/774 ,  G06V10/80 ,  G06V40/12

    Abstract: Enhanced training data representative of possible inputs is used to train a machine learning system. For example, a machine learning system to determine identity based on an image of a human palm may be trained using enhanced training data comprising images. The enhanced training data may comprise source images that have been modified to appear to depict synthetic artifacts that attempt to simulate human palms, augmented images of dirty hands, and so forth. A synthetic artifact image may be produced by selectively removing some data from a source image. An augmented image may be produced by selectively blending the source image with features extracted from sample images. These images may then be used as training data to train the machine learning system.

    System for detecting and mitigating fraudulent biometric input
    22.
    发明授权
    System for detecting and mitigating fraudulent biometric input 有权

    公开(公告)号：US11854301B1

    公开(公告)日：2023-12-26

    申请号：US18296807

    申请日：2023-04-06

    Applicant: AMAZON TECHNOLOGIES, INC.

    Inventor： Manoj Aggarwal ,  Brad Musick ,  Gerard Guy Medioni ,  Rui Zhao ,  Zhen Han

    IPC: G06V40/12 ,  G06V40/50 ,  G06V40/13

    CPC classification number: G06V40/1394 ,  G06V40/1312 ,  G06V40/1318 ,  G06V40/1388 ,  G06V40/50

    Abstract: A person may attempt to gain access to a facility via transaction data, such as images of a hand of the person or other identifying information as acquired by an input device. Possible fraud may be detected by comparing the transaction data with previously stored exclusion data. The exclusion data may include known bad data or synthetic trained data for detecting possible fraud. If the biometric input matches or is similar to the exclusion data, possible fraud is detected and the person is prompted for additional data. The reply data acquired from the person is compared with the exclusion data to determine if possible fraud is still detected. If so, additional prompts are presented to the person until the reply data provides enough confidence of no fraud or until the transaction is terminated.

    System for multi-modal anomaly detection
    24.
    发明授权
    System for multi-modal anomaly detection 有权

    公开(公告)号：US11804060B1

    公开(公告)日：2023-10-31

    申请号：US17443365

    申请日：2021-07-26

    Applicant: AMAZON TECHNOLOGIES, INC.

    Inventor： Rui Zhao ,  Manoj Aggarwal ,  Gerard Guy Medioni ,  Dilip Kumar

    IPC: G06V40/10 ,  G06F18/21 ,  G06F18/2415 ,  G06V40/14

    CPC classification number: G06V40/107 ,  G06F18/2193 ,  G06F18/2415 ,  G06V40/10 ,  G06V40/117 ,  G06V40/14

    Abstract: A pair of input images acquired using a first modality and a second modality is processed using a multi-classifier trained to determine classification data indicative of whether the pair is normal or abnormal. A pair may be deemed abnormal if one or both input images are obscured or inconsistent with one another. Training data comprising normal and abnormal images are used to train the multi-classifier. During training, the multi-classifier uses an objective function that includes cross entropy loss, distance loss, and discrepancy loss to process the training data. During use, the trained multi-classifier processes a pair of input images. If the resulting classification data indicates the pair of input images are normal, the pair of input images may be processed to assert an identity.

    System for determining embedding from multiple inputs
    26.
    发明授权
    System for determining embedding from multiple inputs 有权

    公开(公告)号：US11670104B1

    公开(公告)日：2023-06-06

    申请号：US17097707

    申请日：2020-11-13

    Applicant: AMAZON TECHNOLOGIES, INC.

    Inventor： Lior Zamir ,  Miriam Farber ,  Igor Kviatkovsky ,  Nadav Israel Bhonker ,  Manoj Aggarwal ,  Gerard Guy Medioni

    IPC: G06V10/46 ,  G06V40/10 ,  G06V40/13

    CPC classification number: G06V40/11 ,  G06V10/469 ,  G06V40/13 ,  G06V40/117

    Abstract: A scanner acquires a set of images of a hand of a user to facilitate identification. These images may vary, due to changes in relative position, pose, lighting, obscuring objects such as a sleeve, and so forth. A first neural network determines output data comprising a spatial mask and a feature map for individual images in the set. The output data for two or more images is combined to provide aggregate data that is representative of the two or more images. The aggregate data may then be processed using a second neural network, such as convolutional neural network, to determine an embedding vector. The embedding vector may be stored and associated with a user account. At a later time, images acquired from the scanner may be processed to produce an embedding vector that is compared to the stored embedding vector to identify a user at the scanner.

    System for synthesizing data
    27.
    发明授权
    System for synthesizing data 有权

    公开(公告)号：US11537813B1

    公开(公告)日：2022-12-27

    申请号：US17038648

    申请日：2020-09-30

    Applicant: AMAZON TECHNOLOGIES, INC.

    Inventor： Igor Kviatkovsky ,  Nadav Israel Bhonker ,  Alon Shoshan ,  Manoj Aggarwal ,  Gerard Guy Medioni

    IPC: G06K9/62 ,  G06N20/00 ,  G06V10/145 ,  G06V40/13 ,  G06V40/12

    Abstract: During a training phase, a first machine learning system is trained using actual data, such as multimodal images of a hand, to generate synthetic image data. During training, the first system determines latent vector spaces associated with identity, appearance, and so forth. During a generation phase, latent vectors from the latent vector spaces are generated and used as input to the first machine learning system to generate candidate synthetic image data. The candidate image data is assessed to determine suitability for inclusion into a set of synthetic image data that may be used for subsequent use in training a second machine learning system to recognize an identity of a hand presented by a user. For example, the candidate synthetic image data is compared to previously generated synthetic image data to avoid duplicative synthetic identities. The second machine learning system is then trained using the approved candidate synthetic image data.

    Utilizing sensor data for automated user identification
    28.
    发明授权
    Utilizing sensor data for automated user identification 有权

    公开(公告)号：US10902237B1

    公开(公告)日：2021-01-26

    申请号：US16446404

    申请日：2019-06-19

    Applicant: Amazon Technologies, Inc.

    Inventor： Manoj Aggarwal ,  Jason Garfield ,  Korwin Jon Smith ,  Jordan Tyler Williams

    IPC: G06K9/00 ,  G06K9/62

    Abstract: This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system and updating enrollment data of these users over time. To enroll in the user-recognition system, the user may initially scan his or her palm. The resulting image data may later be used when the user requests to be identified by the system by again scanning his or her palm. However, because the characteristics of user palms may change over the time, the user-recognition system may continue to build more and more data for use in recognizing the user, in addition to removing older data that may no longer accurately represent current characteristics of respective user palms.

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