搜索资源列表
rs-classify
- 几篇和遥感图像分类有关的论文从知网上下的
Image_Classify
- 遥感影像分类的matlab实现（源码+图像）。以及分类后评价（总体精度、Kappa系数、混淆矩阵）。-Remote Sensing Image Classification of matlab implementation (source code+ images). After the evaluation and classification (overall accuracy, Kappa coefficient, confusion matrix).
leipingjun
- 利用类平均距离法，对遥感图像进行分类，操作时调用函数-Use the average distance category, the classification of remote sensing images, call the function when
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- SVM结合模糊方法在遥感图像分类中的应用-SVM combined with fuzzy method in the application of remote sensing image classification
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- 人工神经网络及其在盐田水体遥感图像分类中的研究-Artificial Neural Network and Its Application in salt water in the study of remote sensing image classification
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- 用于高光谱遥感图像分类的空间约束高斯过程方法-For high-spectral remote sensing image classification method of spatial constraints Gaussian process
fenlei1
- 利用提出的纹理灰度值进行最小距离分类遥感图像-Using the proposed minimum distance of gray value texture classification of remote sensing image
Multi-class-SVM-Image-Classification
- 基于神经网络的遥感图像分类取得了较好的效果,但存在固有的过学习、易陷入局部极小等缺点.支持向量机机器学习方法,根据结构风险最小化(SRM)原理,表现出很多优于其他传统方法的性能,本研究的基于多类支持向量机分类器的遥感图像分类取得了达95.4 的分类精度.但由于遥感图像分类类别多,所需训练样本较大,人工选择效率较低,为此提出以人工选择初始聚类质心、C均值模糊聚类算法自动标注训练样本的基于多类支持向量机的半监督式遥感图像分类方法,期望能在获得适用的分类精度的基础上有效提高分类效率-Neural ne
BP
- 基于matlab R2010a的BP神经网络在遥感图像分类中的应用源代码-Application source code matlab R2010a BP neural network-based remote sensing image classification
BP-Classification
- 基于matlab神经网络的遥感图像分类，使用了BP神经网络-Matlab neural network-based remote sensing image classification using BP neural network
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- 用于遥感图像分类处理的一个基于C++的遗传算法聚类程序-For remote sensing image classification based on genetic algorithm clustering procedure of the C++
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- 一种基于纹理特征分析的遥感图像分类C++程序-Based on the analysis of texture characteristics of remote sensing image classification C++ program
Active-Learning
- 遥感图像分类工具箱，包含多种基于支持向量机分类器的主动学习算法-active learning toolbox, used for remote sensing data classification, includes most popular svm-based active learning algorithms.
SOM
- 基于matlab的自组织神经网络进行遥感图像分类处理-Matlab based on the self-organizing neural network for remote sensing image classification processing
Kmean1
- 用于遥感图像分类。其输入为几幅遥感图像，使用k-mean聚类方法对图像中的不同地形进行聚类分割--For remote sensing image classification. Their input for a number of remote sensing images, the use of k-mean clustering method to image the topography of the different cluster partition
yuancode
- 主动学习用于遥感图像的最新论文，对应学习主动学习在遥感图像分类有很好的借鉴意义。-Active learning for remote sensing images of the latest papers, correspondence learning active learning in remote sensing image classification have a good reference
ELMexam
- 使用极限学习机ELM算法进行遥感图像分类的源代码，很好的例子-Use extreme learning machine ELM remote sensing image classification algorithm source code, a good example
LDA
- 模式识别LDA算法代码,基于LDA降维的遥感图像分类，使得降维后的数据具有最好的类别可分性。-LDA pattern recognition algorithm code
DR_LDA
- 基于LDA降维的遥感图像分类，LDA算法函数程序，可与各种分类算法结合，提高图像分类的速率-remote sensing image cut down dimension algorithm based on LDA.
2-separability-based-feature-s
- 2快速separability-based特征选择方法highdimensional遥感图像分类模式识别_guo_pattrec 41(8)1670 - 1670 1670 -2 A fast separability-based feature selection method for highdimensional remotely-sensed image classification Pattern Recognition 41 (8) 1670-1679 2008