INFORMATION PROCESSING APPARATUS AND INFORMATION PROCESSING METHOD

    公开(公告)号:US20230396564A1

    公开(公告)日:2023-12-07

    申请号:US18454477

    申请日:2023-08-23

    CPC classification number: H04L47/805 H04L47/823 H04L47/83

    Abstract: An information processing apparatus comprises a controller. The controller is configured to execute: acquiring a plurality of datasets, each of the datasets being configured with a combination of training data and a correct answer label; and implementing machine learning of an estimation model using the acquired plurality of datasets, wherein the training data includes workload information about an application constructed based on a microservice architecture and resource use information about resources used for each of components included in the application, in a learning target environment, the correct answer label is configured to show a true value of quality of service of the application, and the machine learning comprises training the estimation model such that, for each of the datasets, an estimated value of the quality of service calculated with the estimation model based on the training data corresponds to the true value shown by the correct answer label.

    3D POINT CLOUD-BASED DEEP LEARNING NEURAL NETWORK ACCELERATION APPARATUS AND METHOD

    公开(公告)号:US20230376756A1

    公开(公告)日:2023-11-23

    申请号:US18199995

    申请日:2023-05-22

    CPC classification number: G06N3/08

    Abstract: Disclosed is a 3D point cloud-based deep learning neural network acceleration apparatus including a depth image input unit configured to receive a depth image, a depth data storage unit configured to store depth data derived from the depth image, a sampling unit configured to sample the depth image in units of a sampling window having a predetermined first size, a grouping unit configured to generate a grouping window having a predetermined second size and to group inner 3D point data by grouping window, and a convolution computation unit configured to separate point feature data and group feature data, among channel-direction data of 3D point data constituting the depth image, to perform convolution computation with respect to the point feature data and the group feature data, to sum the results of convolution computation by group grouped by the grouping unit, and to derive the final result.

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