Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation
Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation
复制标题
基于物理模拟的漂浮海洋生物质扭曲态分级机
DOI：
10.1007/978-3-319-08338-4_59
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Masahito Yamamoto and Masashi Furukawa
中科院分区：
文献类型：
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作者：
Jun Ogawa;HIroyuki Iizuka;Masahito Yamamoto and Masashi Furukawa
本文介绍了新的方法来分类海藻捻。由于定性扭转的定义是一个难题，目前还没有定量评价复杂物体扭转变形的方法。海藻的扭曲是这些问题之一。在本文中，我们提出了三个因素（物理，几何和时间因素的扭曲）的扭曲状态的特征，我们开发了基于这些因素的扭曲状态分类器。另外，通过分析实验验证了该分类器对扭体状态的分类准确性。
This paper describes new approaches for classifying twist of seaweeds. There are no evaluation measures of the twist formation of complicated objects quantitatively because the definition of a qualitative twist is a difficult problem. The twist of seaweeds is one of these problems. In this paper, we propose three factors (physical, geometric, and time factor of twist) for characterizing the twist state, and we develop the twist-state classifier based on these factors. Additionally, the analysis experiment verifies how the classifier shows the classification accuracy of twist state.