지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2023.4
- 수록면
- 314 - 319 (6page)
- DOI
- 10.5302/J.ICROS.2023.23.0007
이용수
초록· 키워드
오류제보하기
Warhead arena fragmentation test is a test used for analyzing a warhead’s lethal effect on the target by using fragmentation data such as speed, mass, and distribution. Detecting objects from a high-speed video that captures fragments just to penetrate a target plate in arena test, vision-based fragmentation detection system acquires fragment velocities and fragmentation distribution. Because only the first penetration data must be obtained to determine the velocity, in this study, the bounding box filter-based detector was used to remove the consecutive duplicate detection result. However, the bounding box filter has an additional dummy area surrounding the fragment area; if new detection occurs in this dummy area, it gets removed by the bounding box filter. This decreases the data acquisition rate and hinders a tester from obtaining sufficient fragmentation data for analyzing the warhead effect. In this paper, a pixel-level filter was proposed based on convolutional long short-term memory (convLSTM); the proposed filter utilizes a spatial association loss function for filtering out duplicate results. Owing to the spatial association loss function, which yields a strong correlation between successive frames, the convLSTM-based filter can generate pixel-level filter masks and remove duplicate results effectively. The experimental results demonstrated the superior performance of the filter.
목차
Abstract
I. 서론
II. 탄두 파편데이터 검출시스템
III. Proposed Method
IV. 시험결과
V. 결론
REFERENCES
참고문헌 (6)
참고문헌 신청
B. Zecevic, J. Terzic, A. Catovic, and S. Serdarevic-Kadic, “Characterization of distribution parameters of fragment mass and number for conventional projectiles," Proceedings of the 14th Seminar on New Trends in Research of Energetic Materials, Czech Rep
B. Zecevic, J. Terzic, A. Catovic, and S. Serdarevic-Kadic, “Influencing parameters on HE projectiles with natural fragmentation," Proceedings of the 9th Seminar on New Trends in Research of Energetic Materials, Czech Republic, pp. 780-795, 206.
H. Lee, C. Jung, Y. Park, W. Park, and J. Son, “A new image processing-based fragment detection approach for arena fragmentation test," Journal of the Korea Institute of Military Science and Technology, vol. 22, no. 5, pp. 599-606, Oct 2019.
H. Lee, J. Kim, C. Jung, Y. Park, W. Park, and J. Son, “A deep learning-based fragment detection approach for the arena fragmentation test," Applied Sciences, vol. 10, no. 14, Jul 2020.
X. Shi, Z. Chen, H. Wang, D.-Y. Yeung, W.-k. Wong, and W.-c. Woo, “Convolutional LSTM network: A machine learning approach for precipitation nowcasting," Advances in Neural Information Processing Systems, vol. 28, 2015.
B. Zecevic, J. Terzic, A. Catovic, and S. Serdarevic-Kadic, “Influencing parameters on HE projectiles with natural fragmentation," Proceedings of the 9th Seminar on New Trends in Research of Energetic Materials, Czech Republic, pp. 780-795, 206.
H. Lee, C. Jung, Y. Park, W. Park, and J. Son, “A new image processing-based fragment detection approach for arena fragmentation test," Journal of the Korea Institute of Military Science and Technology, vol. 22, no. 5, pp. 599-606, Oct 2019.
H. Lee, J. Kim, C. Jung, Y. Park, W. Park, and J. Son, “A deep learning-based fragment detection approach for the arena fragmentation test," Applied Sciences, vol. 10, no. 14, Jul 2020.
X. Shi, Z. Chen, H. Wang, D.-Y. Yeung, W.-k. Wong, and W.-c. Woo, “Convolutional LSTM network: A machine learning approach for precipitation nowcasting," Advances in Neural Information Processing Systems, vol. 28, 2015.
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