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基于自适应监督式局部线性嵌入的植物叶片识别算法研究
Alternative TitleRecognition algorithm for plant leaves based on adaptive neighborhood optimization supervised locally linear embedding
阎庆; 梁栋; 张东彦; 王秀
Department其他
Source Publication农业工程技术
ISSN1673-5404
2016
Issue15Pages:80
Contribution Rank1
Keyword监督式局部线性嵌入 流行学习 Fisher投影 临近自适应 叶片识别 精准农业
Abstract局部线性嵌入(LLE)算法在实际应用中存在显著的缺陷,其中之一就是必须确定近邻参数k。本研究提出一种新的监督自适应LLE算法。根据Fisher投影距离构造了一个相似判断准则,用它设置阈值来帮助选择参数k。不同的样本可以根据其所处数据区域分布的密集程度自适应地选择不同的k值。将这种方法应用于植物叶片分类识别中,试验结果表明叶片平均识别率达到了92.4%,优于传统的LLE和监督的LLE方法。
Other AbstractLocally linear embedding (LLE) algorithm has a distinct deficiency in practical application. It requires users to select the neighborhood parameter, k, which denotes the number of nearest neighbors. A new adaptive method is presented based on supervised LLE in this article. A similarity measure is formed by utilizing the Fisher projection distance, and then it is used as a threshold to select k. Different samples will produce different k adaptively according to the density of the data distribution. The method is applied to classify plant leaves. The experimental results show that the average classification rate of this new method is up to 92.4%, which is much better than the results from the traditional LLE and supervised LLE.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20195
Collection其他
Corresponding Author张东彦
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
Recommended Citation
GB/T 7714
阎庆,梁栋,张东彦,等. 基于自适应监督式局部线性嵌入的植物叶片识别算法研究[J]. 农业工程技术,2016(15):80.
APA 阎庆,梁栋,张东彦,&王秀.(2016).基于自适应监督式局部线性嵌入的植物叶片识别算法研究.农业工程技术(15),80.
MLA 阎庆,et al."基于自适应监督式局部线性嵌入的植物叶片识别算法研究".农业工程技术 .15(2016):80.
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