Raw Metrics and Rankings for "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing"

These datasets accompany the article published in <em>Remote Sensing </em>entitled: "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing". For each of the three segmentation models presented in the paper (DTSM, SVM and CIVE) two types of datasets are included: <strong>Raw Metrics: </strong>the raw evaluations for each image returned by each of the 12 evaluation metrics. <strong>Rankings:</strong> the ranking of each image in the dataset based on its raw evaluation. This dataset has been created by sorting in ascending order the dissimilarity metrics (GCE and HDD) and descending order the similarity metrics (all the other metrics). The datasets are in Excel (.xlsx) format and can be easily loaded in R and used to reproduce the results presented in the article.本数据集配套发表于期刊《遥感》（Remote Sensing）的题为《逐像素图像分割指标探索性分析及其在近距离传感中的应用》的论文。本文中共介绍了三款分割模型：DTSM、支持向量机（SVM）以及CIVE，针对每款模型均包含两类数据集：<strong>原始指标值：</strong>由12项评估指标针对每张图像输出的原始评估结果；<strong>排序结果：</strong>数据集中每张图像基于其原始评估值生成的排序。本数据集通过以下方式构建：将相异度指标（GCE与HDD）按升序排列，其余相似度指标则按降序排列。所有数据集均采用Excel（.xlsx）格式，可轻松导入R语言中，用于复现论文中展示的实验结果。