基于单一分类器和集成分类器的VHR图像分类分析

M. G. Lacerda, E. H. Shiguemori, A. Damiao, C. S. Anjos, M. Habermann
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引用次数: 0

摘要

目前,图像分类器种类繁多,但在超高分辨率(VHR)图像的分类精度和处理时间方面仍存在一些问题。另一个问题涉及单个或集成分类器的使用。当然,要考虑的主要因素是分类图像的质量,但计算成本也很重要,特别是在需要实时处理的应用程序中。在这种情况下,本文旨在将7个单一分类器的准确率和同一分类器的集成与处理时间联系起来。在本文中,分类器集成在准确率方面效果最好,但在处理时间方面,决策树表现最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of VHR Image Classification by Single and Ensemble of Classifiers
Given the wide variety of image classifiers available nowadays, some questions remain about the accuracy and processing time of Very High Resolution (VHR) images. Another question concerns the use of a Single or Ensemble Classifiers. Of course, the main factor to consider is the quality of the classified image, but computational cost is also important, especially in applications that require real-time processing. Given this scenario, this paper aims to relate the accuracy of seven single classifiers and the ensemble of the same classifiers with the processing time. In this paper the ensemble of classifiers had the best results in terms of accuracy, however, it comes to processing time, the decision tree had the best performance.
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