Continuous parametrizations of neural network layer weights

    公开(公告)号:US12093830B2

    公开(公告)日:2024-09-17

    申请号:US16976805

    申请日:2019-07-23

    Applicant: Google LLC

    CPC classification number: G06N3/084 G06F18/213 G06N3/048 G06N3/08

    Abstract: Methods, systems, and apparatus for more efficiently and accurately generating neural network outputs, for instance, for use in classifying image or audio data. In one aspect, a method includes processing a network input using a neural network including multiple neural network layers to generate a network output. One or more of the neural network layers is a conditional neural network layer. Processing a layer input using a conditional neural network layer to generate a layer output includes obtaining values of one or more decision parameters of the conditional neural network layer. The neural network processes the layer input and the decision parameters of the conditional neural network layer to determine values of one or more latent parameters of the conditional neural network layer from a continuous set of possible latent parameter values. The values of the latent parameters specify the values of the conditional layer weights.

    Hand gesture recognition based on detected wrist muscular movements

    公开(公告)号:US12073028B2

    公开(公告)日:2024-08-27

    申请号:US18174358

    申请日:2023-02-24

    Applicant: GOOGLE LLC

    CPC classification number: G06F3/017 G06F1/163 G06F3/014 G06V40/28

    Abstract: Techniques of identifying gestures include detecting and classifying inner-wrist muscle motions at a user's wrist using micron-resolution radar sensors. For example, a user of an AR system may wear a band around their wrist. When the user makes a gesture to manipulate a virtual object in the AR system as seen in a head-mounted display (HMD), muscles and ligaments in the user's wrist make small movements on the order of 1-3 mm. The band contains a small radar device that has a transmitter and a number of receivers (e.g., three) of electromagnetic (EM) radiation on a chip (e.g., a Soli chip. This radiation reflects off the wrist muscles and ligaments and is received by the receivers on the chip in the band. The received reflected signal, or signal samples, are then sent to processing circuitry for classification to identify the wrist movement as a gesture.

    Refined location estimates using ultra-wideband communication links

    公开(公告)号:US11638233B2

    公开(公告)日:2023-04-25

    申请号:US17196093

    申请日:2021-03-09

    Applicant: Google LLC

    Abstract: This document describes systems and techniques to generate refined location estimates using ultra-wideband (UWB) communication links. Mobile devices, such as smartphones, include location sensors to estimate their location. The accuracy of location sensors is generally about 3 meters (or about 10 feet). More accurate location data would allow mobile devices to provide new and improved functionality. The described systems and techniques determine the distance between nearby mobile devices using UWB communication links. A mobile device can then use the distance between the mobile devices to determine their relative locations. By comparing the relative locations of the mobile devices with their location estimates, the mobile device can generate a refined location estimate.

    Fully parallel, low complexity approach to solving computer vision problems

    公开(公告)号:US11037026B2

    公开(公告)日:2021-06-15

    申请号:US16749626

    申请日:2020-01-22

    Applicant: Google LLC

    Abstract: Values of pixels in an image are mapped to a binary space using a first function that preserves characteristics of values of the pixels. Labels are iteratively assigned to the pixels in the image in parallel based on a second function. The label assigned to each pixel is determined based on values of a set of nearest-neighbor pixels. The first function is trained to map values of pixels in a set of training images to the binary space and the second function is trained to assign labels to the pixels in the set of training images. Considering only the nearest neighbors in the inference scheme results in a computational complexity that is independent of the size of the solution space and produces sufficient approximations of the true distribution when the solution for each pixel is most likely found in a small subset of the set of potential solutions.

    Fully parallel, low complexity approach to solving computer vision problems

    公开(公告)号:US10579905B2

    公开(公告)日:2020-03-03

    申请号:US15925141

    申请日:2018-03-19

    Applicant: Google LLC

    Abstract: Values of pixels in an image are mapped to a binary space using a first function that preserves characteristics of values of the pixels. Labels are iteratively assigned to the pixels in the image in parallel based on a second function. The label assigned to each pixel is determined based on values of a set of nearest-neighbor pixels. The first function is trained to map values of pixels in a set of training images to the binary space and the second function is trained to assign labels to the pixels in the set of training images. Considering only the nearest neighbors in the inference scheme results in a computational complexity that is independent of the size of the solution space and produces sufficient approximations of the true distribution when the solution for each pixel is most likely found in a small subset of the set of potential solutions.

    TOUCH PRESSURE INPUT FOR DEVICES
    30.
    发明申请

    公开(公告)号:US20220350419A1

    公开(公告)日:2022-11-03

    申请号:US17302258

    申请日:2021-04-28

    Applicant: GOOGLE LLC

    Abstract: A computing device, such as a wearable device, may include at least two electrodes mounted on a body. The computing device may determine an electrical signal associated with a circuit that includes the at least two electrodes and the user. A pressure applied to at least one electrode of the at least two electrodes may be determined from the electrical signal, and at least one function of the computing device may be implemented, based on the pressure.

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