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    Identifying consumers via facial recognition to provide services
    2.
    发明授权
    Identifying consumers via facial recognition to provide services 有权

    公开(公告)号：US10733587B2

    公开(公告)日：2020-08-04

    申请号：US15143451

    申请日：2016-04-29

    Applicant: GOOGLE LLC

    Inventor： Sashikanth Chandrasekaran ,  Denise Ho ,  Dmitry Kalenichenko ,  Varouj Chitilian ,  Timothy Raymond Zwiebel ,  Jumana Al Hashal

    IPC: G06Q20/20 ,  G06K9/00 ,  G07F9/02 ,  G06K9/62

    Abstract: A user signs into an application via a user computing device at a merchant system location. The user computing device receives an identifier from a beacon device at the location to transmit to an account management system. The account management system transmits facial templates to the merchant camera device for users who are signed in to the application in range of the merchant beacon device. The user approaches a point of sale device to purchase a restricted product or service. The merchant camera device compares a captured facial image against the received facial templates to identify the user. A merchant POS device operator, after determining that the user is eligible for the restricted product or service based on account information of the user, selects a payment account of the user. The merchant POS device transmits transaction details to the account management system, which processes the transaction with an issuer system.

    Efficient convolutional neural networks and techniques to reduce associated computational costs
    4.
    发明授权
    Efficient convolutional neural networks and techniques to reduce associated computational costs 有权

    公开(公告)号：US11157815B2

    公开(公告)日：2021-10-26

    申请号：US16524410

    申请日：2019-07-29

    Applicant: Google LLC

    Inventor： Andrew Gerald Howard ,  Bo Chen ,  Dmitry Kalenichenko ,  Tobias Christoph Weyand ,  Menglong Zhu ,  Marco Andreetto ,  Weijun Wang

    IPC: G06N3/08 ,  G06N3/04

    Abstract: The present disclosure provides systems and methods to reduce computational costs associated with convolutional neural networks. In addition, the present disclosure provides a class of efficient models termed “MobileNets” for mobile and embedded vision applications. MobileNets are based on a straight-forward architecture that uses depthwise separable convolutions to build light weight deep neural networks. The present disclosure further provides two global hyper-parameters that efficiently trade-off between latency and accuracy. These hyper-parameters allow the entity building the model to select the appropriately sized model for the particular application based on the constraints of the problem. MobileNets and associated computational cost reduction techniques are effective across a wide range of applications and use cases.

    Identifying consumers in a transaction via facial recognition
    5.
    发明授权
    Identifying consumers in a transaction via facial recognition 有权

    公开(公告)号：US10726407B2

    公开(公告)日：2020-07-28

    申请号：US15462772

    申请日：2017-03-17

    Applicant: Google LLC

    Inventor： Sashikanth Chandrasekaran ,  Dmitry Kalenichenko ,  Timothy Raymond Zwiebel

    IPC: G06Q20/00 ,  G06Q20/20 ,  G06Q20/32 ,  G06Q20/40 ,  G06K9/00 ,  G06T7/73

    Abstract: A merchant and a user register with a payment processing system, which establishes a facial template based on a user image. The user signs into a payment application via a user computing device, which receives an identifier from a merchant beacon device to transmit to the payment processing system. The payment processing system transmits facial templates to the merchant camera device for other users who are also signed in to the payment application in range of the merchant beacon device. The merchant camera device compares a captured facial image against the received facial templates to identify the user. A merchant POS device operator selects an account of the user. The merchant POS device transmits transaction details to the payment processing system, which processes the transaction with an issuer system. The payment processing system receives an approval of the transaction authorization request and transmits a receipt to the merchant POS device.

    GENERATING OBJECT EMBEDDINGS FROM IMAGES
    8.
    发明申请
    GENERATING OBJECT EMBEDDINGS FROM IMAGES 审中-公开

    公开(公告)号：US20200242333A1

    公开(公告)日：2020-07-30

    申请号：US16842920

    申请日：2020-04-08

    Applicant: Google LLC

    Inventor： Gerhard Florian Schroff ,  Dmitry Kalenichenko ,  Keren Ye

    IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an object embedding system. In one aspect, a method comprises providing selected images as input to the object embedding system and generating corresponding embeddings, wherein the object embedding system comprises a thumbnailing neural network and an embedding neural network. The method further comprises backpropagating gradients based on a loss function to reduce the distance between embeddings for same instances of objects, and to increase the distance between embeddings for different instances of objects.

    Generating object embeddings from images
    9.
    发明授权
    Generating object embeddings from images 有权

    公开(公告)号：US10657359B2

    公开(公告)日：2020-05-19

    申请号：US15818124

    申请日：2017-11-20

    Applicant: Google LLC

    Inventor： Gerhard Florian Schroff ,  Dmitry Kalenichenko ,  Keren Ye

    IPC: G06K9/00 ,  G06N3/04 ,  G06N3/08 ,  G06K9/46 ,  G06K9/62

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an object embedding system. In one aspect, a method comprises providing selected images as input to the object embedding system and generating corresponding embeddings, wherein the object embedding system comprises a thumbnailing neural network and an embedding neural network. The method further comprises backpropagating gradients based on a loss function to reduce the distance between embeddings for same instances of objects, and to increase the distance between embeddings for different instances of objects.

    Memory-Guided Video Object Detection
    10.
    发明申请
    Memory-Guided Video Object Detection 有权

    公开(公告)号：US20220189170A1

    公开(公告)日：2022-06-16

    申请号：US17432221

    申请日：2019-02-22

    Applicant: Google LLC

    Inventor： Menglong Zhu ,  Mason Liu ,  Marie Charisse White ,  Dmitry Kalenichenko ,  Yinxiao Li

    IPC: G06V20/40 ,  G06V10/70 ,  G06V10/80 ,  G06V10/82 ,  G06V10/94 ,  G06V10/776 ,  G06V10/774

    Abstract: Systems and methods for detecting objects in a video are provided. A method can include inputting a video comprising a plurality of frames into an interleaved object detection model comprising a plurality of feature extractor networks and a shared memory layer. For each of one or more frames, the operations can include selecting one of the plurality of feature extractor networks to analyze the one or more frames, analyzing the one or more frames by the selected feature extractor network to determine one or more features of the one or more frames, determining an updated set of features based at least in part on the one or more features and one or more previously extracted features extracted from a previous frame stored in the shared memory layer, and detecting an object in the one or more frames based at least in part on the updated set of features.

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