中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

7 records (took 0.016 seconds)

    DEBLURRING METHOD AND APPARATUS BASED ON UNSUPERVISED LEARNING AND LATENT SPACE PROCESSING
    2.
    发明申请
    DEBLURRING METHOD AND APPARATUS BASED ON UNSUPERVISED LEARNING AND LATENT SPACE PROCESSING 有权

    公开(公告)号：US20250069195A1

    公开(公告)日：2025-02-27

    申请号：US18757222

    申请日：2024-06-27

    Applicant: Electronics and Telecommunications Research Institute

    Inventor： Hyun Yong Lee ,  Seok Kap Ko ,  Nack Woo Kim ,  JUNGI LEE ,  YUMIN HWANG

    IPC: G06T5/60 ,  G06T5/73

    Abstract: The present invention relates to a deblurring method and apparatus based on unsupervised learning and latent space processing. An unsupervised learning method of a deblurring model according to the present invention includes inputting an input image into a deblurring model to generate a restored image, calculating an error between the input image and the restored image, and training the deblurring model based on the error. A latent space processing-based deblurring method according to the present invention includes inputting a deblurring target image into an encoder, applying an image filtering technique to an output of the encoder, and inputting the output of the encoder, to which the image filtering technique has been applied, into a decoder to generate a deblurred image.

    Method of managing system health
    4.
    发明授权
    Method of managing system health 有权

    公开(公告)号：US12222798B2

    公开(公告)日：2025-02-11

    申请号：US17965537

    申请日：2022-10-13

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Nack Woo Kim ,  Byung Tak Lee ,  Jun Gi Lee ,  Hyun Yong Lee

    IPC: G06F11/00 ,  G06F18/2132 ,  G06N3/04 ,  G06N3/08

    Abstract: A method of managing system health is provided. The method includes calculating a reconstruction missing value with respect to the second domain data, determining a degree of degradation of the system on the basis of the reconstruction missing value, predicting a second remaining useful life (RUL) prediction value {tilde over (y)} of the system on the basis of the second domain data, based on a result of the determination of the degree of degradation, optimizing a degradation compensation function on the basis of a distribution of a first RUL prediction value y of the system predicted based on the first domain data in a pre-learning process of the diagnosis model, and predicting a final RUL prediction value {tilde over (y)}′ obtained by compensating for the second RUL prediction value {tilde over (y)}, by using the optimized degradation compensation function.

Patent Agency Ranking