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Matching Pursuit方法，经典的稀疏表示方法，可以用人脸识别和图像分类，图像去噪，现在非常流行。-Matching Pursuit method, sparse representation of the classic, you can use face recognition and image classification, image denoising, now very popular.
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提出一种基于分形理论和BP 神经网络的航空遥感图像有监督分类方法。该方法尝试将航空图像
的光谱信息和纹理特征相结合。它首先将彩色航空图像由RGB 格式转化为HSI 格式,然后,根据亮度计算分
数维、多重分形广义维数谱q-D( q) 和“空隙”等基于分形的纹理特征,同时加入归一化的色度和饱和度作为光
谱特征,采用BP 神经网络作为分类器。通过对彩色航空图像的分类实验,结果证实该方法行之有效。-Based on fractal theory and BP neural network
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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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几篇关于神经网络的文章，结合遥感图像的特性，介绍了人工神经网络在遥感图像分类中的作用-Several articles on the neural network, combined with the characteristics of remote sensing images on the artificial neural networks in remote sensing image classification in the role of
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fourier descr iptor for image processing computer vision to describe shape for classification-fourier descr iptor for image processing computer vision to describe shape for classification
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k-means clustering for image classification
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基于特征选择和svms的图像分类 MI算法-Feature selection and image classification svms
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将ＳＶＭ应用到医学图像分类中，建立分类器-The SVM applied to medical image classification, the establishment of classification
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Image segmentation: classification-neural network, SVM,-Image segmentation: classification-neural network, SVM,...
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传统的基于像素的统计特征的分类方法在处理高分辨率影像的分类问题上遇到了很大的困
难。介绍了面向对象与基于像素的分类方法 ,探讨了基于面向对象的遥感影像的模糊分类方法在地
物分类中的新思路。并且通过了展示利用 ecognition 进行的的一个分类实例 ,阐述了面向对象的模
糊分类技术的软件应用-Traditional pixel-based classification of the statistical characteristics of high-resolution ima
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Image Classification Using SVMs
describe SVM
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图像分类算法，2012年CVPR中的文章，效果还可以，采用“Local Naive Bayes Nearest Neighbor”方法-Image classification algorithm, CVPR 2012 article, the effect can also " Local Naive Bayes Nearest Neighbor method
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Textural Features for Image Classification-Texture is one of the important characteristics used in
identifying objects or regions of interest in an image, whether the image
be a photomicrograph, an aerial photograph, or a satellite image. This
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此文档包含对卷积神经网络的描述及在图像处理中的应用，对学习卷积神经网络有重要帮助。-The work presented here
uses image classifi cation performance (accurate discrimination between common
classes of objects) as a basis for comparing visual system models, and algorithms
for fi
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Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification
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基于压缩感知的纹理图像分类，介绍了一种新的高效算法：分类压缩感知。与一般压缩感知及其他方法在四大纹理数据库上对比。有原文献及自己的译文-Introduced a new efficient algorithm based on compressed sensing texture image classification, compressed sensing: Category. Original literature and translation
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适用于SIFT图像特征提取、K-means生成聚类、SVM图像分类-Image feature extraction, generation clustering, image classification
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基于商空间粒度计算的SAR图像分类方法研究-SAR Image Classification Based on Granularity Computing of
Quotient Space Theory
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Hyperspectral image classification with limited
number of labeled pixels is a challenging task. In this paper, we
propose a bilayer graph-based learning framework to address
this problem. For graph-based classification, how to establish
the n
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Sar Image classification
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