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    Probabilistic in-memory computing
    1.
    发明授权
    Probabilistic in-memory computing 有权

    公开(公告)号：US11900979B2

    公开(公告)日：2024-02-13

    申请号：US17508818

    申请日：2021-10-22

    Applicant: INTEL CORPORATION

    Inventor： Hai Li ,  Dmitri E. Nikonov ,  Punyashloka Debashis ,  Ian A. Young ,  Mahesh Subedar ,  Omesh Tickoo

    IPC: G11C11/16 ,  G06F7/544 ,  G11C11/54 ,  G06N3/045 ,  G06N3/047

    CPC classification number: G11C11/1673 ,  G06F7/5443 ,  G06N3/045 ,  G06N3/047 ,  G11C11/1675 ,  G11C11/1697 ,  G11C11/54

    Abstract: Embodiments of the present disclosure are directed toward probabilistic in-memory computing configurations and arrangements, and configurations of probabilistic bit devices (p-bits) for probabilistic in-memory computing. concept with emerging. A probabilistic in-memory computing device includes an array of p-bits, where each p-bit is disposed at or near horizontal and vertical wires. Each p-bit is a time-varying resistor that has a time-varying resistance, which follows a desired probability distribution. The time-varying resistance of each p-bit represents a weight in a weight matrix of a stochastic neural network. During operation, an input voltage is applied to the horizontal wires to control the current through each p-bit. The currents are accumulated in the vertical wires thereby performing respective multiply-and-accumulative (MAC) operations. Other embodiments may be described and/or claimed.

    POST-INCIDENT MANAGEMENT FOR AUTONOMOUS VEHICLES
    4.
    发明申请
    POST-INCIDENT MANAGEMENT FOR AUTONOMOUS VEHICLES 审中-公开

    公开(公告)号：US20190051015A1

    公开(公告)日：2019-02-14

    申请号：US15869933

    申请日：2018-01-12

    Applicant: Intel Corporation

    Inventor： David Gonzalez Aguirre ,  Omar Florez ,  Julio Zamora Esquivel ,  Mahesh Subedar ,  Javier Felip Leon ,  Rebecca Chierichetti ,  Andrea Johnson ,  Glen Anderson

    IPC: G06T7/80 ,  G06T7/00 ,  G06T7/32

    Abstract: In one example a management system for an autonomous vehicle, comprises a first image sensor to collect first image data in a first geographic region proximate the autonomous vehicle and a second image sensor to collect second image data in a second geographic region proximate the first geographic region and a controller communicatively coupled to the first image sensor and the second image sensor and comprising processing circuitry to collect the first image data from the first image sensor and second image data from the second image sensor, generate a first reliability index for the first image sensor and a second reliability index for the second image sensor, and determine a correlation between the first image data and the second image data. Other examples may be described.

    Joint Enhancement of Lightness, Color and Contrast of Images and Video
    5.
    发明申请
    Joint Enhancement of Lightness, Color and Contrast of Images and Video 审中-公开
    联合增强图像和视频的亮度，颜色和对比度

    公开(公告)号：US20150235348A1

    公开(公告)日：2015-08-20

    申请号：US14704116

    申请日：2015-05-05

    Applicant: Intel Corporation

    Inventor： Abhijit Sarkar ,  Jorge E. Caviedes ,  Mahesh Subedar

    IPC: G06T5/00 ,  H04N1/60

    CPC classification number: G06T5/00 ,  G06T5/003 ,  G06T5/007 ,  G06T2207/10016 ,  G06T2207/10024 ,  H04N1/6005 ,  H04N1/6027 ,  H04N1/608

    Abstract: In some embodiments, color and contrast enhancement video processing may be done in one shot instead of adjusting one of color and contrast enhancement, then the other, and then going back to the first one to readjust because of the second adjustment. In some embodiments, global lightness adjustment, local contrast enhancement, and saturation enhancement may be done at the same time and in parallel. Lightness adjustment improves visibility of details for generally dark or generally light images without changing intended lighting conditions in the original shot, and is used to enhance the range of color/saturation enhancement. Local contrast enhancement done in parallel improves visual definition of objects and textures and thus local contrast and perceived sharpness.

    Abstract translation: 在一些实施例中，可以一次进行颜色和对比度增强视频处理，而不是调整颜色和对比度增强之一，然后调整另一个，然后返回到第一个以由于第二调整而重新调整。 在一些实施例中，可以同时并行地进行全局亮度调整，局部对比度增强和饱和度增强。 亮度调整提高了一般黑暗或一般较轻的图像的细节的可视性，而不改变原始照片中的预期照明条件，并且用于增强色彩/饱和度增强的范围。 并行的局部对比度增强可以提高对象和纹理的视觉定义，从而提高局部对比度和感知锐度。

    METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO GENERATE FLOW AND AUDIO MULTI-MODAL OUTPUT
    6.
    发明公开
    METHODS, SYSTEMS, ARTICLES OF MANUFACTURE AND APPARATUS TO GENERATE FLOW AND AUDIO MULTI-MODAL OUTPUT 审中-公开

    公开(公告)号：US20240256839A1

    公开(公告)日：2024-08-01

    申请号：US18635844

    申请日：2024-04-15

    Applicant: Intel Corporation

    Inventor： Jiaxiang Jiang ,  Mahesh Subedar

    IPC: G06N3/047 ,  G06N3/0464

    CPC classification number: G06N3/047 ,  G06N3/0464

    Abstract: Methods, systems, articles of manufacture, apparatus and methods are disclosed to generate flow and audio multi-modal output. An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit programmed by the machine-readable instructions to train an unsupervised image model to generate flow tensors based on a reference frame and a driver frame, the flow tensors representing at least one of rotation information or translation information. The example apparatus also includes at least one processor circuit programmed by the machine-readable instructions to train a denoising diffusion probabilistic model (DDPM) based on (a) the flow tensors, (b) audio distributions and (c) prompt signals, the trained DDPM to temporally align the flow tensors with the audio distributions.

    DETECTION OF ANOMALIES IN THREE-DIMENSIONAL IMAGES
    9.
    发明申请
    DETECTION OF ANOMALIES IN THREE-DIMENSIONAL IMAGES 有权

    公开(公告)号：US20240412366A1

    公开(公告)日：2024-12-12

    申请号：US18812700

    申请日：2024-08-22

    Applicant: Intel Corporation

    Inventor： Jiaxiang Jiang ,  Athmanarayanan Lakshmi Narayanan ,  Nilesh Ahuja ,  Ibrahima Jacques Ndiour ,  Ergin Utku Genc ,  Mahesh Subedar ,  Omesh Tickoo

    IPC: G06T7/00

    Abstract: Systems, apparatus, articles of manufacture, and methods to detect anomalies in three-dimensional (3D) images are disclosed. Example apparatus disclosed herein generate a first two-dimensional (2D) anomaly map corresponding to a first 2D image slice of a 3D image, the first 2D image slice corresponding to a first axis of the 3D image. Disclosed example apparatus also generate a second 2D anomaly map corresponding to a second 2D image slice of the 3D image, the second 2D image slice corresponding to a second axis of the 3D image. Disclosed example apparatus further generate a 3D anomaly volume based on the first 2D anomaly map and the second 2D anomaly detection, the 3D anomaly volume corresponding to the 3D image.

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