INFORMATION PROCESSING SYSTEM AND INFORMATION PROCESSING METHOD

    公开(公告)号:US20240045636A1

    公开(公告)日:2024-02-08

    申请号:US18381420

    申请日:2023-10-18

    IPC分类号: G06F3/14 G06V10/74 G09G5/373

    摘要: An imaging control device includes an image acquiring part that acquires a first training image of a machine learning model, a display control part that causes a display device to display the first training image based on a distance between the display device and an imaging device that acquires a blurred image, an imaging control part that causes the imaging device to capture the first training image to acquire a second training image, and a storage control part that stores a data set including a set of the second training image and correct answer information. The display control part changes, when the distance is changed, a display size of the first training image so that a size of the second training image acquired by the imaging device is maintained. The imaging control part causes the imaging device to capture the first training image when the distance is changed.

    INFORMATION PROCESSING SYSTEM AND INFORMATION PROCESSING METHOD

    公开(公告)号:US20240087301A1

    公开(公告)日:2024-03-14

    申请号:US18508994

    申请日:2023-11-14

    摘要: An imaging control device includes a correct answer information acquiring part that acquires first correct answer information corresponding to a training image of a machine learning model from a first storage part, a correct answer image display control part that causes a display device to display a first correct answer image based on the first correct answer information, an imaging control part that causes an imaging device that acquires a blurred image to capture the first correct answer image displayed on the display device and acquires a second correct answer image, a correct answer information generating part that generates second correct answer information based on the second correct answer image, and a storage control part that stores a data set including a set of the training image and the second correct answer information in a second storage part.

    CONTROL SYSTEM AND CONTROL METHOD

    公开(公告)号:US20220207857A1

    公开(公告)日:2022-06-30

    申请号:US17553137

    申请日:2021-12-16

    IPC分类号: G06V10/60 G06N20/00 G06V10/14

    摘要: A control device includes a parameter acquisition unit that acquires an augmentation parameter regarding geometric augmentation or optical augmentation of training data to be used for training a machine learning model, a display controller that causes a display device to display an image based on the augmentation parameter, an imaging controller that causes an imaging device to capture the displayed image, and an output unit that outputs the captured image obtained by the imaging device as the training data.

    TRAINING METHOD, TRAINING SYSTEM, AND NON-TRANSITORY COMPUTER READABLE RECORDING MEDIUM STORING TRAINING PROGRAM

    公开(公告)号:US20240311635A1

    公开(公告)日:2024-09-19

    申请号:US18675806

    申请日:2024-05-28

    IPC分类号: G06N3/08 G06V10/776 G06V10/82

    CPC分类号: G06N3/08 G06V10/776 G06V10/82

    摘要: The training system determines a plurality of sensor parameter candidates to be used for an operation of a sensor, generates a plurality of sensor data sets corresponding to each of the plurality of sensor parameter candidates and including sensor data to be obtained by the operation of the sensor and a plurality of pieces of correct answer identification information corresponding to each of the sensor data, generates a plurality of trained neural network model candidates corresponding to the plurality of sensor parameter candidates, calculates identification performance of the plurality of trained neural network model candidates, selects a pair of the trained neural network model candidate with the highest identification performance and the sensor parameter candidate corresponding to the trained neural network model candidate with the highest identification performance, and outputs the selected pair of the sensor parameter candidate and the trained neural network model candidate.