인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
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AI 아이디어
AI 리더
AI 뷰어
Citeasy
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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.9 No.6
- 발행연도
- 2014.11
- 수록면
- 2,154 - 2,161 (8page)
이용수
초록· 키워드
Growth analysis and selection of sea cucumbers (Stichopus japonicas) is typically performed through length or weight measurements. However, because sea cucumbers continuously change shape depending on the external environment, weight measurement has been the preferred approach. Weight measurements require extensive time and labor, moreover it is often difficult to accurately weigh sea cucumbers because of their wet surface. The present study measured sea cucumber features, including the body length, width, and thickness, by using a vision system and regression analysis to generate R² values that were used to develop a weight estimation algorithm. The R² value between the actual volume and weight of the sea cucumbers was 0.999, which was relatively high. Evaluation of the performance of this algorithm using cross-validation showed that the root mean square error and worst-case prediction error were 1.434 g and ±5.879 g, respectively. In addition, the present study confirmed that the proposed weight estimation algorithm and single slide rail device for weight measurement can measure weights at approximately 4,500 sea cucumbers per hour.
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목차
- Abstract
- 1. Introduction
- 2. Material and Methods
- 3. Results and Discussion
- 4. Conclusion
- References
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2015-500-002703860
