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基于BP神经网络的高分辨率遥感影像分类处理 文档-High-resolution remote sensing image classification based on BP neural network
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遥感图像处理算法介绍，包括分类、融合、植物检测、变化检测等算法的具体介绍，是编程的基础和遥感的基础知识。-Remote sensing image processing algorithms introduced, including classification, fusion, specific descr iption of the plant detection, change detection algorithm is the basis of the programming and
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将matlab应用于基于纹理特征的遥感影像分类中的标准差分类-Matlab applied to the differential classification based on texture features of the remote sensing image classification standard
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基于云模型的高光谱遥感图像的分类研究Cloud model based remote sensing image classification research-Cloud model based remote sensing image classification research
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利用bp神经网络对遥感图像进行分类，输入样本值后，根据样本值对遥感图像不同的地物进行分类，分类后计算每种地物所占面积-The use of bp neural network classification of remote sensing images, enter a sample value, based on the sample value of the different features of remote sensing image classification, classif
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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
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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
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对遥感影像进行增强，平滑去噪等，还包括K均值分类-Remote sensing image enhancement, denoising, also including the K-means classification
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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
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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
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利用核函数进行遥感图像的分类，本程序再支持向量机的基础上引入了核函数进行图像分类，是分类效果更加明显-Use of nuclear function remote sensing image classification, the program no longer support vector machine based on the introduction of the kernel function for image classification, classification eff
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一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。-A semi-supervised SVM is presented for the classification of remote sensing images. The
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一个K-Means算法，可实现对遥感图像的分类处理-A K-Means algorithm can be realized on remote sensing image classification
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一个K-Means算法，可实现对遥感图像的分类处理-A K-Means algorithm can be realized on remote sensing image classification
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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
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remote sensing image analysis done by segmentation and classification is done finally
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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
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基于vc6.0的遥感图像处理，可以实现图像增强，植被指数计算，K均值分类等功能。-Vc6.0 based remote sensing image processing and image enhancement can be achieved, vegetation index calculation, K-means classification capabilities.
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高分辨率遥感影像的支持张量机分类方法，此方法能够利用少量的训练样本实现更优的分类精度。-Support tensor machines resolution remote sensing image classification method, and this method can use a small amount of training samples to achieve better classification accuracy.
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