NEURAL NETWORK PROCESSING
    31.
    发明公开

    公开(公告)号:US20230316063A1

    公开(公告)日:2023-10-05

    申请号:US17708474

    申请日:2022-03-30

    Applicant: Arm Limited

    CPC classification number: G06N3/08 G06N3/04 G06K9/6201

    Abstract: An input data array is subjected to neural network processing to generate a result of the neural network processing for the input data array. A perturbation is applied to a part (but not all of) the input data array, with neural network processing then performed using the so-perturbed version of the input data array. However only some (and not all) of the perturbed version is subjected to neural network processing, based on the part of the input data array to which the perturbation has been applied. The result of the neural network processing of the perturbed version of the input data array is compared with the result of the neural network processing of the input data array without the perturbation, to determine whether the perturbation of the input data array has an effect on the result of the neural network processing.

    Data processing using a neural network system

    公开(公告)号:US11699064B2

    公开(公告)日:2023-07-11

    申请号:US16392391

    申请日:2019-04-23

    CPC classification number: G06N3/04

    Abstract: A neural network system executable on a processor. The neural network system, when executed on the processor, comprises a merged layer shareable between a first neural network and a second neural network. The merged layer is configured to receive input data from a prior layer of at least one of the first and second neural networks. The merged layer is configured to apply a superset of weights to the input data to generate intermediate feature data representative of at least one feature of the input data, the superset of weights being combined from a first set of weights associated with the first neural network and a second set of weights associated with the second neural network. The merged layer is also configured to output the intermediate feature data to at least one subsequent layer, the at least one subsequent layer serving the first and second neural networks.

    Neural network processing
    36.
    发明授权

    公开(公告)号:US11625578B2

    公开(公告)日:2023-04-11

    申请号:US16834881

    申请日:2020-03-30

    Abstract: A method apparatus and computer readable medium for processing input data using a neural network comprising at least a first layer and a second layer. The method comprising the steps of applying a partitioning scheme to the input data, to partition the input data into a plurality of blocks, each block representing a portion of the input data. At the first layer of the neural network, the blocks of the input data are processed in a first order to generate intermediary data, wherein the intermediary data is partitioned into a plurality of intermediary blocks. At the second layer of the neural network, the intermediary blocks are processed in a second order, wherein the second order differs from the first order.

    Vehicle-assist system
    37.
    发明授权

    公开(公告)号:US11584378B2

    公开(公告)日:2023-02-21

    申请号:US17081786

    申请日:2020-10-27

    Applicant: Arm Limited

    Inventor: Daren Croxford

    Abstract: A vehicle-assist system comprising one or more sensors to monitor an environment of a vehicle and an eye-tracking system, including an eye-tracking sensor, to determine a gaze characteristic of a driver of the vehicle. The vehicle-assist system is to detect a hazard, and determine a hazard location of the hazard, in the environment of the vehicle. Based on the hazard location and the gaze characteristic of the driver, the vehicle-assist system is to output an indication of the hazard to the driver.

    SYSTEM, DEVICES AND/OR PROCESSES FOR AUGMENTING ARTIFICIAL INTELLIGENCE AGENT AND COMPUTING DEVICES

    公开(公告)号:US20220391685A1

    公开(公告)日:2022-12-08

    申请号:US17337317

    申请日:2021-06-02

    Applicant: Arm Limited

    Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to enhance capabilities of peer devices. In an implementation, at least one agent to: identify one or more learnable capabilities enabled by one or more parameters that are accessible via receipt of one or more message at the one or more communication devices from one or more other computing devices; and determine a utility of augmenting at least one of the one or more learning engines with at least one of the one or more learnable capabilities.

    Head-mounted display
    39.
    发明授权

    公开(公告)号:US11500204B2

    公开(公告)日:2022-11-15

    申请号:US16896853

    申请日:2020-06-09

    Applicant: Arm Limited

    Abstract: A head-mounted display (HMD) comprising a first side for facing a user of the HMD, a second side opposite to the first side, and a reflective layer for at least partially reflecting incident light incident on the second side. At least one processor of the HMD is configured to obtain luminance data indicative of a luminance of the incident light and control a display device, based on the luminance data, to control a luminance of a portion of emitted light directed towards the user of the HMD during the display of the image. Further examples relate to an HMD with a display device configured to emit light of at least one predetermined wavelength range during display of an image by the display device, and a layer arranged to at least partially prevent transmission of the light of the at least one predetermined wavelength range outward from the HMD.

    Data processing method and system for performing convolutions

    公开(公告)号:US11423117B2

    公开(公告)日:2022-08-23

    申请号:US16552548

    申请日:2019-08-27

    Abstract: A computer implemented method for performing convolutions between subsets of an input data array and a kernel resulting in subsets of an output data array. The method may include receiving an input data array and using positional data indicating the position of elements of the input data array to determine subsets of the input data array which contains at least one non-zero value data element; performing convolutions between the subsets of the input data array containing at least one non-zero value data element and a kernel to produce output data array subsets; and combining the output data subsets with the positional data to generate output data indicative of a completed output data array.

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