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    System and method enabling one-hot neural networks on a machine learning compute platform
    12.
    发明授权
    System and method enabling one-hot neural networks on a machine learning compute platform 有权

    公开(公告)号：US11481218B2

    公开(公告)日：2022-10-25

    申请号：US16633071

    申请日：2017-08-02

    Applicant: Intel Corporation

    Inventor： Jianguo Li ,  Yurong Chen

    IPC: G06F9/30 ,  G06N3/063 ,  G06N3/04

    Abstract: One embodiment provides for a compute apparatus to perform machine learning operations, the compute apparatus comprising instruction decode logic to decode a single instruction including multiple operands into a single decoded instruction, the multiple operands including a first operand and a second operand, the first operand including vector of one-hot coded weights and the second operand including a vector of input data; and a general-purpose graphics compute unit including a first logic unit, the general-purpose graphics compute unit to execute the single decoded instruction, wherein to execute the single decoded instruction includes to perform multiple operations on the first set of operands and the second set of operands.

    3D facial capture and modification using image and temporal tracking neural networks
    13.
    发明授权
    3D facial capture and modification using image and temporal tracking neural networks 有权

    公开(公告)号：US11308675B2

    公开(公告)日：2022-04-19

    申请号：US16971132

    申请日：2018-06-14

    Applicant: Intel Corporation

    Inventor： Shandong Wang ,  Ming Lu ,  Anbang Yao ,  Yurong Chen

    IPC: G06T13/40 ,  G06N3/08 ,  G06T19/20 ,  G06K9/00 ,  G06K9/62 ,  G06N3/04

    Abstract: Techniques related to capturing 3D faces using image and temporal tracking neural networks and modifying output video using the captured 3D faces are discussed. Such techniques include applying a first neural network to an input vector corresponding to a first video image having a representation of a human face to generate a morphable model parameter vector, applying a second neural network to an input vector corresponding to a first and second temporally subsequent to generate a morphable model parameter delta vector, generating a 3D face model of the human face using the morphable model parameter vector and the morphable model parameter delta vector, and generating output video using the 3D face model.

    JOINT TRAINING OF NEURAL NETWORKS USING MULTI-SCALE HARD EXAMPLE MINING
    14.
    发明申请
    JOINT TRAINING OF NEURAL NETWORKS USING MULTI-SCALE HARD EXAMPLE MINING 有权

    公开(公告)号：US20210133518A1

    公开(公告)日：2021-05-06

    申请号：US16491735

    申请日：2017-04-07

    Applicant: INTEL CORPORATION

    Inventor： Anbang Yao ,  Yun Ren ,  Hao Zhao ,  Tao Kong ,  Yurong Chen

    IPC: G06K9/68 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

    Abstract: An example apparatus for mining multi-scale hard examples includes a convolutional neural network to receive a mini-batch of sample candidates and generate basic feature maps. The apparatus also includes a feature extractor and combiner to generate concatenated feature maps based on the basic feature maps and extract the concatenated feature maps for each of a plurality of received candidate boxes. The apparatus further includes a sample scorer and miner to score the candidate samples with multi-task loss scores and select candidate samples with multi-task loss scores exceeding a threshold score.

    VISUAL QUESTION ANSWERING USING VISUAL KNOWLEDGE BASES
    15.
    发明申请
    VISUAL QUESTION ANSWERING USING VISUAL KNOWLEDGE BASES 有权

    公开(公告)号：US20210109956A1

    公开(公告)日：2021-04-15

    申请号：US16650853

    申请日：2018-01-30

    Applicant: INTEL CORPORATION

    Inventor： Zhou Su ,  Jianguo Li ,  Yinpeng Dong ,  Yurong Chen

    IPC: G06F16/332 ,  G06N3/04 ,  G06N5/02 ,  G06K9/32

    Abstract: An example apparatus for visual question answering includes a receiver to receive an input image and a question. The apparatus also includes an encoder to encode the input image and the question into a query representation including visual attention features. The apparatus includes a knowledge spotter to retrieve a knowledge entry from a visual knowledge base pre-built on a set of question-answer pairs. The apparatus further includes a joint embedder to jointly embed the visual attention features and the knowledge entry to generate visual-knowledge features. The apparatus also further includes an answer generator to generate an answer based on the query representation and the visual-knowledge features.

    DISTRIBUTED NEURAL NETWORKS FOR SCALABLE REAL-TIME ANALYTICS
    19.
    发明申请
    DISTRIBUTED NEURAL NETWORKS FOR SCALABLE REAL-TIME ANALYTICS 审中-公开
    分布式实时分析神经网络

    公开(公告)号：US20170076195A1

    公开(公告)日：2017-03-16

    申请号：US14849924

    申请日：2015-09-10

    Applicant: Intel Corporation

    Inventor： Shao-Wen Yang ,  Jianguo Li ,  Yen-Kuang Chen ,  Yurong Chen

    IPC: G06N3/04

    CPC classification number: G06N3/063 ,  G06N3/0454

    Abstract: Techniques related to implementing distributed neural networks for data analytics are discussed. Such techniques may include generating sensor data at a device including a sensor, implementing one or more lower level convolutional neural network layers at the device, optionally implementing one or more additional lower level convolutional neural network layers at another device such as a gateway, and generating a neural network output label at a computing resource such as a cloud computing resource based on optionally implementing one or more additional lower level convolutional neural network layers and at least implementing a fully connected portion of the neural network.

    Abstract translation: 讨论了与分布式神经网络实现数据分析相关的技术。 这样的技术可以包括在包括传感器的设备处生成传感器数据，所述传感器在设备处实现一个或多个下级卷积神经网络层，可选地在诸如网关的另一设备上实现一个或多个附加的较低级卷积神经网络层，以及生成 基于可选地实现一个或多个附加的较低级卷积神经网络层并且至少实现神经网络的完全连接的部分，在计算资源（例如云计算资源）处的神经网络输出标签。

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