yuqingXing/leave_data

一百种植物叶子数据集。该数据集源自一篇关于使用形状、纹理和边缘特征进行植物叶子分类的论文。数据集包含1600个样本，每个样本有64个特征向量，分为形状、纹理和边缘三个特征文件。每个样本的特征向量后面跟着类别标签，共有100个类别，每个类别有16个样本，没有缺失值。

Dataset of 100 Plant Leaf Species. This dataset is derived from a paper focused on plant leaf classification using shape, texture and edge features. It comprises 1600 samples, with each sample containing 64 feature vectors, and is split into three feature files for shape, texture and edge features respectively. Each sample's feature vectors are followed by its class label. In total, there are 100 classes, with 16 samples per class, and no missing values are present in the dataset.

原始信息汇总

数据集概述

任务类别

• 图像分类

语言

• 英语

标签

• 生物学

数据集大小

• 10M<n<100M

数据集来源

• 原始所有者：James Cope, Thibaut Beghin, Paolo Remagnino, Sarah Barman
• 数据集捐赠者：Charles Mallah, James Cope

数据集信息

• 包含1600个样本，每个样本有16个样本属于100个不同的叶类，无缺失值。
• 每个样本包含三个特征：形状、纹理和边缘，每个特征对应一个64元素的向量。
• 数据文件包括：
  • data_Sha_64.txt：基于形状的预测
  • data_Tex_64.txt：基于纹理的预测
  • data_Mar_64.txt：基于边缘的预测

参考文献

• [1] Charles Mallah, James Cope, James Orwell. Plant Leaf Classification Using Probabilistic Integration of Shape, Texture and Margin Features. Signal Processing, Pattern Recognition and Applications, in press.
• [2] J. Cope, P. Remagnino, S. Barman, and P. Wilkin. Plant texture classification using gabor co-occurrences. Advances in Visual Computing, pages 699-677, 2010.
• [3] T. Beghin, J. Cope, P. Remagnino, and S. Barman. Shape and texture based plant leaf classification. In: Advanced Concepts for Intelligent Vision Systems, pages 345-353. Springer, 2010.

搜集汇总

背景与挑战

背景概述

该数据集是一个包含100种植物叶片样本的分类数据集，每个样本提供形状、边缘和纹理三个特征的64维向量描述，共计1600个数据点。数据集源自多篇学术研究，专注于植物叶片的特征分析和分类任务。