Objects and Features Neural Network
    1.
    发明申请

    公开(公告)号:US20200034976A1

    公开(公告)日:2020-01-30

    申请号:US16049107

    申请日:2018-07-30

    Abstract: Examples include detecting objects and determining a set of features for the objects. Examples include receiving a first image input, generating a number of feature maps from the first image input using a number of convolution filters, generating a first number of fully connected layers directly based on the number of feature maps, and detecting a number of objects in the first image and determining a set of features for each object from the first number of fully connected layers.

    Video active region batching
    2.
    发明授权

    公开(公告)号:US11074453B2

    公开(公告)日:2021-07-27

    申请号:US15884939

    申请日:2018-01-31

    Abstract: An example video analytics device can include a memory, a processor executing instructions stored in the memory, an active region detector to identify a plurality of active regions of a plurality of video streams, wherein the plurality of active regions are sections in the plurality of video streams that change from a first frame to a second frame, and a bin packer communicatively coupled with the processor to combine the plurality of active regions to produce a multi-batch of an individual slice, wherein the multi-batch of the individual slice is a batch including the plurality of active regions that is processed at once.

    Objects and features neural network

    公开(公告)号:US11158063B2

    公开(公告)日:2021-10-26

    申请号:US16049107

    申请日:2018-07-30

    Abstract: Examples include detecting objects and determining a set of features for the objects. Examples include receiving a first image input, generating a number of feature maps from the first image input using a number of convolution filters, generating a first number of fully connected layers directly based on the number of feature maps, and detecting a number of objects in the first image and determining a set of features for each object from the first number of fully connected layers.

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