VEHICLE-MOUNTED PROCESSING DEVICE OF LEARNING-USE DATA

    公开(公告)号:US20220001884A1

    公开(公告)日:2022-01-06

    申请号:US17319097

    申请日:2021-05-13

    IPC分类号: B60W50/06 G06N3/08

    摘要: A vehicle-mounted processing device of learning-use data including a data acquisition unit acquiring data relating to operation of the vehicle, a neural network storage unit storing a neural network which outputs output values relating to operational control of the vehicle if data which was acquired at the data acquisition unit is input, and a learning-use data storage unit storing learning-use data of weights of the neural network. If the frequency of learning of the weights of the neural network on the vehicle or the frequency of transmission of the learning-use data to the server becomes lower, the amount of storage per unit time of the learning-use data successively stored in the learning-use data storage unit or the amount of the learning-use data which finishes being stored in the learning-use data storage unit is made to decrease.

    MACHINE LEARNING APPARATUS, MACHINE LEARNING SYSTEM, MACHINE LEARNING METHOD, AND PROGRAM

    公开(公告)号:US20210390406A1

    公开(公告)日:2021-12-16

    申请号:US17343736

    申请日:2021-06-10

    IPC分类号: G06N3/08 G06K9/62

    摘要: A machine learning apparatus includes an acquisition unit that acquires third data including first data and second data, the first data including at least one of parameter data collected for a plurality of collection devices and teacher data created from the parameter data, and the second data which are associated with the first data and which represent collection conditions of the parameter data; a selection unit that selects specific data from the third data; and a learning unit that performs machine learning using the specific data, and generates a trained model which is to be used for a target device. Further, the selection unit selects the specific data which are associated with the collection conditions in which a difference between usage conditions of the trained model for the target device and the collection conditions in the collection devices is equal to or less than a predetermined reference.