公开(公告)号：US11682213B2

公开(公告)日：2023-06-20

申请号：US17235537

申请日：2021-04-20

Applicant: Electronics and Telecommunications Research Institute

Inventor： Hyun Jin Yoon ,  Mi Kyong Han

IPC: G06K9/00 ,  G06V20/52 ,  G06N3/08 ,  G06F18/214 ,  G06F18/2415 ,  G06F18/2431 ,  G06V10/764 ,  G06V10/82 ,  G06V20/70

CPC classification number: G06V20/52 ,  G06F18/2155 ,  G06F18/2415 ,  G06F18/2431 ,  G06N3/08 ,  G06V10/764 ,  G06V10/82 ,  G06V20/70

Abstract: The present disclosure provides a method and a device for training a neural network model for use in analyzing captured images, and an intelligent image capturing apparatus employing the same. The neural network model can be trained by performing the image reconstruction and the image classification using based on image data received from a plurality of image capturing devices installed in the monitoring area, calculating at least one loss function based on data processed by the neural network model or the neural network model training device, and determining parameters minimizing the loss function. In addition, the neural network model can be updated through the re-training taking into account the newly acquired image data. Accordingly, the image analysis neural network model can operate with high precision and accuracy.