Image signal processor and electronic device and electronic system including the same

    公开(公告)号:US11418737B2

    公开(公告)日:2022-08-16

    申请号:US17404198

    申请日:2021-08-17

    Abstract: An image processing device including a memory; and at least one image signal processor configured to: generate, using a first neural network, a feature value indicating whether to correct a global pixel value sensed during a unit frame interval, and generate a feature signal including the feature value; generate an image signal by merging the global pixel value with the feature signal; split a pixel value included in the image signal into a first sub-pixel value and a second sub-pixel value, split a frame feature signal included in the image signal into a first sub-feature value corresponding to the first sub-pixel value and a second sub-feature value corresponding to the second sub-pixel value, and generate a first sub-image signal including the first sub-pixel value and the first sub-feature value, and a second sub-image signal including the second sub-pixel value and the second sub-feature value; and sequentially correct the first sub-image signal and the second sub-image signal using a second neural network.

    Image processing device including neural network processor and operating method thereof

    公开(公告)号:US11533458B2

    公开(公告)日:2022-12-20

    申请号:US15930615

    申请日:2020-05-13

    Abstract: An image processing device includes: an image sensor configured to generate first image data by using a color filter array; and processing circuitry configured to select a processing mode from a plurality of processing modes for the first image data, the selecting being based on information about the first image data; generate second image data by reconstructing the first image data using a neural network processor based on the processing mode; and generate third image data by post-processing the second image data apart from the neural network processor based on the processing mode.

    Method of detecting object in image and image processing device

    公开(公告)号:US09818022B2

    公开(公告)日:2017-11-14

    申请号:US14965027

    申请日:2015-12-10

    CPC classification number: G06K9/00228 G06K9/6203 G06K9/6257 G06K9/6292

    Abstract: At least one example embodiment discloses a method of detecting an object in an image. The method includes receiving an image, generating first images for performing a first classification operation based on the received image, reviewing first-image features of the first images using a first feature extraction method with first-type features, first classifying at least some of the first images as second images, the classified first images having first-image features matching the first-type features, reviewing second-image features of the second images using a second feature extraction method with second-type features, second classifying at least some of the second images as third images, the classified second images having second-image features matching the second-type features and detecting an object in the received image based on results of the first and second classifying.

    Artificial neural network model and electronic device including the same

    公开(公告)号:US11544813B2

    公开(公告)日:2023-01-03

    申请号:US16822188

    申请日:2020-03-18

    Inventor: Irina Kim

    Abstract: An electronic device is described, that includes a processing logic configured to receive input image data and generate output image data having a different format from the input image data using an artificial neural network model. The artificial neural network model includes a plurality of encoding layer units, including a plurality of layers located at a plurality of levels, respectively. The artificial neural network model also includes a plurality of decoding layer units including a plurality of layers and configured to form skip connections with the plurality of encoding layer units at the same levels. A first encoding layer unit of a first level receives a first input feature map and outputs a first output feature map. A first output feature map is based on the first input feature map, to a subsequent encoding layer unit and a decoding layer unit at the first level.

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