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Alternative TitleRecognition algorithm for plant leaves based on adaptive neighborhood optimization supervised locally linear embedding
阎庆; 梁栋; 张东彦; 王秀
Source Publication农业工程技术
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
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.
Document Type期刊论文
Corresponding Author张东彦
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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