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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
Review of Algorithms for Behavior Detection and Threat Evaluation of Hostile Targets in Combat Situations |
ÀúÀÚ(Author) |
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Soo Yong Lee
Juwon Kim
Sangheun Shim
Dong Kuk Ryu
Kiwoong Park
Kijung Shin
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¿ø¹®¼ö·Ïó(Citation) |
VOL 38 NO. 02 PP. 0029 ~ 0041 (2022. 08) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
In combat situations, behavior detection and threat evaluation of hostile targets is of significant value and challenge. Fuzzy logic, Bayesian network, and neural network are widely studied classes of approaches developed for automated behavior detection and threat evaluation in combat situations. In this review, for each approach, we overview its concept, current status of the application research, algorithm variants designed for application, input variables and output format, and their strengths and weaknesses. We find that the up-to-date approaches for behavior detection and threat evaluation are limited in considering interaction among a large number of entities. As a future research direction, we suggest developing dynamic graph neural network-based behavior detection and threat evaluation method.
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Å°¿öµå(Keyword) |
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Threat evaluation
Behavior detection
Neural network
Bayesian network
Fuzzy logic
Graph Neural Network
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