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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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基于小波分析，使用线性回归模型来进行纹理的识别和分类，是08年IEEE TRANSACTION的经典文献。-Based on wavelet analysis, the use of linear regression model for texture identification and classification, 2008 IEEE TRANSACTION are classic literature.
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一种基于最大熵和部件的物体检测方法。在人脸检测上的应用取得了很大的准确率提升。-This paper presents a probabilistic part-based approach for texture and object recognition. Textures are represented using a part dictionary found by quantizing the appearance
of scale- or affine-invariant ke
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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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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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texture based image analysis
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Abstract—Noninvasive ultrasound imaging of carotid plaques
allows for the development of plaque-image analysis methods associated
with the risk of stroke. This paper presents several plaqueimage
analysis methods that have been developed over th
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基于彩色局部二值模式的纹理分类研究，采用LCVBP原理，创新实用-Color texture classification based on local binary pattern studies, using LCVBP prinicple, innovation and practical
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Classification of protein crystal images using svm wavelets and BloBWorld Texture features.
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Texture Classification by Wavelet Packet Signatures
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results than conventional LBP based schemes.
Several observations can be made for CLBP. First, LBP is a
special case of CLBP by using only CLBP_S. Second, we will
show that the sign component preserves more image local
structural information
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有关LBP方法的相关英文文献，可以用来纹理分析和分类，特征提取等-the papers about LBP methods, which can be used for feature extraction, texture classification and analysis
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Texture oriented data mining process classifying the known words and unknown words in a file. This will be coded in c sharp Language it will be provided for data classification/
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efficient LBP Local binary patterns (LBP) is a type of feature used for classification in computer vision. LBP is the particular case of the Texture Spectrum model proposed in 1990.[1][2] LBP was first described in 1994.[3][4] It has since been found
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Texture Analysis Using DWT for Grape Plant Species Classification:-
By observing leaf, we can easily identify plant but it is difficult to identify its species. In this project we developed an algorithm that gives user the ability to identify plan
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该文献是关于旋转不变纹理特征的提取，分类算法-the paper is about rotation invariant texture feature classification algorithm
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核稀疏用于字典学习和稀疏表示，可用于纹理分类等模式识别问题。-Nuclear sparse dictionary for learning and sparse representation can be used for texture classification pattern recognition problem.
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作为一种优秀的纹理特征提取技术，多重分形谱插值方法被提出用于图像的特征提取和分类。-As an excellent texture feature extraction technology, a multi-fractal spectrum interpolation methods have been proposed for image feature extraction and classification.
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