IMAGING DEVICE AND ELECTRONIC DEVICE

    公开(公告)号:US20210151486A1

    公开(公告)日:2021-05-20

    申请号:US16628073

    申请日:2018-07-03

    Abstract: An imaging device capable of executing image processing is provided.
    A structure is employed in which a photoelectric conversion element, a first transistor, a second transistor, and an inverter circuit are included; one electrode of the photoelectric conversion element is electrically connected to one of a source and a drain of the first transistor; the other of the source and the drain of the first transistor is electrically connected to one of a source and a drain of the second transistor; the one of the source and the drain of the second transistor is electrically connected to an input terminal of the inverter circuit; and data obtained by photoelectric conversion is binarized and output.

    IMAGING DEVICE AND ELECTRONIC DEVICE

    公开(公告)号:US20220216254A1

    公开(公告)日:2022-07-07

    申请号:US17705479

    申请日:2022-03-28

    Abstract: An imaging device capable of executing image processing is provided. A structure is employed in which a photoelectric conversion element, a first transistor, a second transistor, and an inverter circuit are included; one electrode of the photoelectric conversion element is electrically connected to one of a source and a drain of the first transistor; the other of the source and the drain of the first transistor is electrically connected to one of a source and a drain of the second transistor; the one of the source and the drain of the second transistor is electrically connected to an input terminal of the inverter circuit; and data obtained by photoelectric conversion is binarized and output.

    IMAGE PROCESSING METHOD, SEMICONDUCTOR DEVICE, AND ELECTRONIC DEVICE

    公开(公告)号:US20200242730A1

    公开(公告)日:2020-07-30

    申请号:US16636705

    申请日:2018-08-23

    Abstract: A semiconductor device which performs upconversion without a large amount of learning data is provided. The semiconductor device increasing the resolution of a first image data to generate a high-resolution image data. It includes the first step of generating a second image data by decreasing the resolution of the first image data, the second step of generating a third image data having a higher resolution than the second image data by inputting the second image data to a neural network, the third step of calculating an error for the third image data relative to the first image data by their comparison, and the fourth step of modifying a weight coefficient of the neural network on the basis of the error; and then the high resolution image data is generated by inputting the first image data into the neural network after a prescribed number of the second to fourth steps.

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