국방 경계감시시스템의 성능향상을 위한개인화 연합학습 기법 적용방안 연구

• 영문명: A Study on the Application of Personalized Federated Learning for Enhancing the Performance of Defense Surveillance Systems
• 발행기관: 한국IT서비스학회
• 저자명: 이규정(Gyuejeong Lee) 최대영(Daeyoung Choi)
• 간행물 정보: 『한국IT서비스학회지』제24권 제3호, 95~106쪽, 전체 12쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

The military operates numerous CCTV systems for surveillance purposes and has recently begun integrating AI technology to improve operational efficiency. Current AI models applied to CCTV systems utilize pre-trained models based on large-scale training data; however, this approach presents several limitations in AI model performance management: restricted continuous and rapid model updates, limited optimization for operational environments, and challenges in model management due to varying AI models across manufacturers. Therefore research on AI learning methods that can overcome these limitations and achieve optimal performance in actual operational environments is necessaryThis study proposes personalized federated learning (PFL) techniques for AI model performance enhancement in CCTV systems based on an analysis of defense surveillance system operational environments. In the proposed approach, AI models in video processing servers with cross-silo characteristics apply identical AI models with PFL techniques based on model weight exchange for customized learning, while AI models in CCTV terminals with cross-device characteristics employ prototype-based PFL techniques. Experimental results confirm that the proposed PFL techniques demonstrate improved performance in classification accuracy and communication efficiency compared to other learning methods. Additionally, we identify environmental considerations for implementing personalized federated learning. The findings of this research are expected to contribute to AI application strategies and planning to maximize defense surveillance system performance in actual operational environments.

목차

1. 서론

2. 이론적 배경

3. 개인화 연합학습 기법의 국방경계감시시스템 적용방안

4. PEL의 성능 개선효과 분석

5. 결론

참고문헌

키워드

Defense Surveillance System Personalized Federated Learning(PFL) CCTV Image Classification Object Detection