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    MOBILE DATA AUGMENTATION ENGINE FOR PERSONALIZED ON-DEVICE DEEP LEARNING SYSTEM
    14.
    发明申请
    MOBILE DATA AUGMENTATION ENGINE FOR PERSONALIZED ON-DEVICE DEEP LEARNING SYSTEM 有权

    公开(公告)号：US20210248722A1

    公开(公告)日：2021-08-12

    申请号：US16946989

    申请日：2020-07-14

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Chenchi Luo ,  Yingmao Li ,  Youngjun Yoo

    IPC: G06T5/00 ,  G06T5/50 ,  G06N3/04 ,  G06T3/40

    Abstract: A method includes processing, using at least one processor of an electronic device, each of multiple images using a photometric augmentation engine, where the photometric augmentation engine performs one or more photometric augmentation operations. The method also includes applying, using the at least one processor, multiple layers of a convolutional neural network to each of the images, where each layer generates a corresponding feature map. The method further includes processing, using the at least one processor, at least one of the feature maps using at least one feature augmentation engine between consecutive layers of the multiple layers, where the at least one feature augmentation engine performs one or more feature augmentation operations.

    APPARATUS AND METHOD FOR DYNAMIC MULTI-CAMERA RECTIFICATION USING DEPTH CAMERA
    15.
    发明申请
    APPARATUS AND METHOD FOR DYNAMIC MULTI-CAMERA RECTIFICATION USING DEPTH CAMERA 有权

    公开(公告)号：US20210174479A1

    公开(公告)日：2021-06-10

    申请号：US16703712

    申请日：2019-12-04

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Yingmao Li ,  Chenchi Luo ,  George Q. Chen ,  Youngjun Yoo

    IPC: G06T5/00 ,  G06T5/40 ,  G06T5/50 ,  G06T7/55 ,  G06T7/73 ,  G06T3/00

    Abstract: A method includes obtaining, using first and second image sensors of an electronic device, first and second images, respectively, of a scene. The method also includes obtaining, using an image depth sensor of the electronic device, a third image and a first depth map of the scene, the first depth map having a resolution lower than a resolution of the first and second images. The method further includes undistorting the first and second images using the third image and the first depth map. The method also includes rectifying the first and second images using the third image and the first depth map. The method further includes generating a disparity map using the first and second images that have been undistorted and rectified. In addition, the method includes generating a second depth map using the disparity map and the first depth map, where the second depth map has a resolution that is higher than the resolution of the first depth map.

    MULTI-TASK FUSION NEURAL NETWORK ARCHITECTURE
    16.
    发明申请
    MULTI-TASK FUSION NEURAL NETWORK ARCHITECTURE 有权

    公开(公告)号：US20210158142A1

    公开(公告)日：2021-05-27

    申请号：US16693112

    申请日：2019-11-22

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Chenchi Luo ,  Yingmao Li ,  Youngjun Yoo

    IPC: G06N3/08 ,  G06N3/04

    Abstract: A method includes identifying, by at least one processor, multiple features of input data using a common feature extractor. The method also includes processing, by the at least one processor, at least some identified features using each of multiple pre-processing branches. Each pre-processing branch includes a first set of neural network layers and generates initial outputs associated with a different one of multiple data processing tasks. The method further includes combining, by the at least one processor, at least two initial outputs from at least two pre-processing branches to produce combined initial outputs. In addition, the method includes processing, by the at least one processor, at least some initial outputs or at least some combined initial outputs using each of multiple post-processing branches. Each post-processing branch includes a second set of neural network layers and generates final outputs associated with a different one of the multiple data processing tasks.

    Hand motion pattern modeling and motion blur synthesizing techniques
    17.
    发明授权
    Hand motion pattern modeling and motion blur synthesizing techniques 有权

    公开(公告)号：US12079971B2

    公开(公告)日：2024-09-03

    申请号：US17666166

    申请日：2022-02-07

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Yingmao Li ,  Hamid R. Sheikh ,  John Seokjun Lee ,  Youngmin Kim ,  Jun Ki Cho ,  Seung-Chul Jeon

    IPC: G06V10/00 ,  G06T5/77

    CPC classification number: G06T5/77 ,  G06T2207/10144 ,  G06T2207/20081 ,  G06T2207/20084

    Abstract: A method includes obtaining, using a stationary sensor of an electronic device, multiple image frames including first and second image frames. The method also includes generating, using multiple previously generated motion vectors, a first motion-distorted image frame using the first image frame and a second motion-distorted image frame using the second image frame. The method further includes adding noise to the motion-distorted image frames to generate first and second noisy motion-distorted image frames. The method also includes performing (i) a first multi-frame processing (MFP) operation to generate a ground truth image using the motion-distorted image frames and (ii) a second MFP operation to generate an input image using the noisy motion-distorted image frames. In addition, the method includes storing the ground truth and input images as an image pair for training an artificial intelligence/machine learning (AI/ML)-based image processing operation for removing image distortions caused by handheld image capture.

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