公开(公告)号：US20230015295A1

公开(公告)日：2023-01-19

申请号：US17550825

申请日：2021-12-14

Applicant: Electronics and Telecommunications Research Institute

Inventor： Ki-Min YUN ,  Jin-Young MOON ,  Jong-Won CHOI ,  Joung-Su YOUN ,  Seok-Jun CHOI ,  Woo-Seok HYUNG

IPC: G06V10/764 ,  G06V20/40 ,  G06V10/762

Abstract: Disclosed herein are an object recognition apparatus and method based on environment matching. The object recognition apparatus includes memory for storing at least one program, and a processor for executing the program, wherein the program performs extracting at least one key frame from a video that is input in real time, determining a similarity between the key frame extracted from the input video and each of videos used as training data of prestored multiple recognition models, based on a pretrained similarity-matching network, and selecting a recognition model pretrained with a video having a maximal similarity to the key frame extracted from the input video, preprocessing the input video such that at least one of color and size of a video used as training data of an initial model is similar to that of the input video, and recognizing the preprocessed video based on the initial model.

公开(公告)号：US20240289455A1

公开(公告)日：2024-08-29

申请号：US18209623

申请日：2023-06-14

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Hyung-Kwan KIM ,  Jong-Won CHOI ,  Seung-Oh CHOI ,  Jeong-Han YUN ,  Won-Seok HWANG ,  Woo-Myo LEE ,  Byung-Gil MIN ,  Hyeok-Ki SHIN

IPC: G06F21/56 ,  G06T7/11 ,  G06V10/40 ,  G06V10/75 ,  G08B21/18

CPC classification number: G06F21/566 ,  G06T7/11 ,  G06V10/40 ,  G06V10/759 ,  G08B21/18

Abstract: Disclosed herein is a method for detecting an anomaly state based on screen output. The method includes receiving the output screen of a target device to be monitored, setting a target region to be examined in the output screen of the target device to be monitored, calculating a feature value vector corresponding to the state of the target region to be examined, calculating an anomaly score using a pretrained auto-encoder by receiving the feature value vector as input, and determining whether the target device to be monitored is anomalous using the anomaly score.