Safeguards-related event detection in surveillance video using semi-supervised learning approach
We develop a deep learning model employing a semi-supervised learning approach, which can detect automatically safeguards-related events in nuclear facility from surveillance video. Our model is designed after a comprehensive analysis of the trends in artificial intelligence-based models to identify...
Saved in:
Main Authors: | Se-Hwan Park, Byung-Hee Won, Seong-Kyu Ahn |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-02-01
|
Series: | Nuclear Engineering and Technology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573324004546 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DRCO: Dense-Label Refinement and Cross Optimization for Semi-Supervised Object Detection
by: Yunlong Qin, et al.
Published: (2025-01-01) -
Study of implicit information semi-supervised learning algorithm
by: Guo-dong LIU, et al.
Published: (2015-10-01) -
UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification
by: Zeyu Ren, et al.
Published: (2024-01-01) -
A Semi-Supervised Learning Approach to Quality-Based Web Service Classification
by: Mehdi Nozad Bonab, et al.
Published: (2024-01-01) -
Fourier Ptychographic Microscopy with Optical Aberration Correction and Phase Unwrapping Based on Semi-Supervised Learning
by: Xuhui Zhou, et al.
Published: (2025-01-01)