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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.13 No.3
- 발행연도
- 2018.5
- 수록면
- 1,377 - 1,382 (6page)
이용수
초록· 키워드
오류제보하기
In the marine environment, many clutters have similar features with the marine targets due to the diverse changes of the air temperature, water temperature, various weather and seasons. Also, the clutters in the ground environment have similar features due to the same reason. In this paper, we proposed a robust Hybrid Machine Character (HMC) method to classify the targets from the clutters in the infrared images for the various environments. The proposed HMC method adopts human’s multiple personality utilization and the CNN ensemble method to classify the targets in the ground and marine environments. This method uses an advantage of the each environmental training model. Experimental results demonstrate that the proposed method has better success rate to classify the targets and clutters than previously proposed CNN classification method.
목차
Abstract
1. Introduction
2. Learning Model for HMC
3. Comparison of HMC Method with Others
4. Conclusion
References
참고문헌 (9)
참고문헌 신청
H. Zhang, Z. Zhao and F. Xiao, “Robust Detection Method of Small Targets in Sea-Clutter via Improved Fast Clustering Segmentation,” 10.1109/IHMSC.2016.236, pp. 123-126, 2016
C. Yang, H. Liu, S. Liao and S. Wang, “Small target detection in infrared video sequence using robust dictionary learning,” Infrared Physics & Technology, vol. 68, pp. 1-9, 2015
S. Qi, J. ma, H. Li, S. Zhang and J. Tian, “Infrared small target enhancement via phase spectrum of Quaternion Fourier Transform,” Infrared Physics & Technology, vol. 62, pp. 50-58, 2014.
Ødegaard, N., Knapskog, A. O., Cochin, C., Louvigne, J. C. “Classification of ships using real and simulated data in a convolutional neural network,” Rader Conference, 2016.
Hiroshi Tasaka, “Everyone has multiple personality,” Kobunsha Co. Japan, 2015.
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