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
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Electrical Engineering and Information Science Journal of Electrical Engineering and Information Science Vol.1 No.2
- 발행연도
- 1996.6
- 수록면
- 27 - 32 (6page)
이용수
초록· 키워드
오류제보하기
In target tracking area, the data association plays an important role and has been studied extensively. In this paper, after defining the data association as a constrained optimization, we introduce a new energy function and thereby an efficient realization of neural networks.
As an application, this algorithm is used to detect object boundaries in IR images. The problem is that the IR image noisy, the shape of the object is variable, and the positions of the end points are not predictable. The performance of this algorithm is discussed with the experimental results.
As an application, this algorithm is used to detect object boundaries in IR images. The problem is that the IR image noisy, the shape of the object is variable, and the positions of the end points are not predictable. The performance of this algorithm is discussed with the experimental results.
목차
Abstract
Ⅰ. Introduction
Ⅱ. A MAP Estimate for Optimal Data Association
Ⅲ. Determining Energy Functions for the MAP
Ⅳ. Minimizing the Energy by Neural Network
Ⅴ. Application to Boundary Detection
Ⅵ. Experimental Results
Ⅶ. Conclusion
References
저자소개
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