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    USING A NEURAL NETWORK
    1.
    发明申请
    USING A NEURAL NETWORK 审中-公开

    公开(公告)号：US20200242470A1

    公开(公告)日：2020-07-30

    申请号：US16756182

    申请日：2018-10-16

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Vlado Menkovski ,  Asif Rahman ,  Caroline Denise Francoise Raynaud ,  Bryan Conroy ,  Dimitrios Mavroeidis ,  Erik Bresch ,  Teun van den Heuvel

    IPC: G06N3/08 ,  G06N20/00 ,  G06K9/62

    Abstract: A method, system and computer-program product for identifying neural network inputs for a neural network that may have been incorrectly processed by the neural network. A set of activation values (of a subset of neurons of a single layer) associated with a neural network input is obtained. A neural network output associated with the neural network input is also obtained. A determination is made as to whether a first and second neural network input share similar sets of activation values, but dissimilar neural network outputs or vice versa. In this way a prediction can be made as to whether one of the first and second neural network inputs has been incorrectly processed by the neural network.

    Using a neural network
    3.
    发明授权
    Using a neural network 有权

    公开(公告)号：US11468323B2

    公开(公告)日：2022-10-11

    申请号：US16756182

    申请日：2018-10-16

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Vlado Menkovski ,  Asif Rahman ,  Caroline Denise Francoise Raynaud ,  Bryan Conroy ,  Dimitrios Mavroeidis ,  Erik Bresch ,  Teun van den Heuvel

    IPC: G06K9/62 ,  G06N3/08 ,  G06N20/00

    Abstract: A method, system and computer-program product for identifying neural network inputs for a neural network that may have been incorrectly processed by the neural network. A set of activation values (of a subset of neurons of a single layer) associated with a neural network input is obtained. A neural network output associated with the neural network input is also obtained. A determination is made as to whether a first and second neural network input share similar sets of activation values, but dissimilar neural network outputs or vice versa. In this way a prediction can be made as to whether one of the first and second neural network inputs has been incorrectly processed by the neural network.

    Apparatus and method for providing a control signal for a blood pressure measurement device
    4.
    发明授权
    Apparatus and method for providing a control signal for a blood pressure measurement device 有权

    公开(公告)号：US10912467B2

    公开(公告)日：2021-02-09

    申请号：US15550915

    申请日：2016-02-18

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Jens Muehlsteff ,  Erik Bresch ,  Teun van den Heuvel ,  Lars Schmitt ,  Dieter Woehrle

    IPC: A61B5/02 ,  A61B5/0225 ,  A61B5/00 ,  A61B5/021 ,  G16H50/30 ,  A61B5/022 ,  A61B8/04

    Abstract: The present invention relates to an apparatus (18) for providing a control signal for a blood pressure measurement device, comprising: an input interface (24) for obtaining a health state parameter being indicative of a health state of a patient (12); a processing unit (28) for determining one or more operation settings of a blood pressure measurement device (14) based on the health state parameter, said one or more operation settings including a parameter that can be adjusted at the blood pressure measurement device (14) when conducting a blood pressure measurement with the device and that affects a precision of said blood pressure measurement and a patient comfort resulting from said blood pressure measurement; and a control interface (30) for providing a control signal for a blood pressure measurement device (14) to perform a blood pressure measurement based on said one or more operation settings. The present invention further relates to a corresponding method. Still further, the present invention relates to a system for monitoring a patient.

    Training first and second neural network models
    5.
    发明授权
    Training first and second neural network models 有权

    公开(公告)号：US11657265B2

    公开(公告)日：2023-05-23

    申请号：US16191542

    申请日：2018-11-15

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Binyam Gebre ,  Erik Bresch ,  Dimitrios Mavroeidis ,  Teun van den Heuvel ,  Ulf Grossekathöfer

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/0481

    Abstract: Described herein are systems and methods for training first and second neural network models. A system comprises a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to set a weight in the second model based on a corresponding weight in the first model, train the second model on a first dataset, wherein the training comprises updating the weight in the second model and adjust the corresponding weight in the first model based on the updated weight in the second model.

    TRAINING FIRST AND SECOND NEURAL NETWORK MODELS
    6.
    发明申请
    TRAINING FIRST AND SECOND NEURAL NETWORK MODELS 审中-公开

    公开(公告)号：US20190156205A1

    公开(公告)日：2019-05-23

    申请号：US16191542

    申请日：2018-11-15

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Binyam Gebre ,  Erik Bresch ,  Dimitrios Mavroeidis ,  Teun van den Heuvel ,  Ulf Grossekathöfer

    IPC: G06N3/08 ,  G06N3/04

    Abstract: Described herein are systems and methods for training first and second neural network models. A system comprises a memory comprising instruction data representing a set of instructions and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to set a weight in the second model based on a corresponding weight in the first model, train the second model on a first dataset, wherein the training comprises updating the weight in the second model and adjust the corresponding weight in the first model based on the updated weight in the second model.

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