Toward an Online Continual Learning Architecture for Intrusion Detection of Video Surveillance-Reference-Cited by-同舟云学术

Toward an Online Continual Learning Architecture for Intrusion Detection of Video Surveillance

Published:2022 Issue: Volume:10 Page:89732-89744
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kwon Beom¹^ORCID,Kim Taewan²

Affiliation:

1. Department of Artificial Intelligence, Dongyang Mirae University, Seoul, South Korea

2. Data Science Major, Dongduk Wonen's University, Seoul, South Korea

Funder

Grant of the Korea Health Technology Research and Development Project through the Korea Health Industry Development Institute (KHIDI), Ministry of Health and Welfare, Republic of Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09864598.pdf?arnumber=9864598

Reference46 articles.

1. Stable multi-target tracking in real-time surveillance video

2. PETS2009: Dataset and challenge

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