搜索资源列表
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利用超限学习机（ELM）和稀疏表示(SRC)进行图像分类。Matlab完整源码。-Extreme learning machine and adaptive sparse representation for image classification
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用来图像分割，特征提取，目标跟踪，分类的工具箱-Used for image segmentation, feature extraction, target tracking and classification of the toolbox
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支持向量机遥感图像分类代码，内含C、matlab代码，参考文献供学习-Support vector machine remote sensing image classification code
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Classic GLCM texture calculation method, Relief computing classification weight, Convolution operation is intended to signal and image rendering.
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This toolbox is meant to facilitate the manipulation of images and video in Matlab. Its purpose is to complement, not replace, Matlab's Image Processing Toolbox, and in fact it requires that the Matlab Image Toolbox be installed. Emphasis has been pl
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对图像特征进行属性约简，找到最适合分类的特征。(Attribute reduction of image features, to find the most suitable features of classification)
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Using matlab to calculate the Mahalanobis distance for the image, Prediction Error Method for Parameter Identification - the idea of relaxation, You can achieve data classification and regression pattern recognition.
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模糊C均值分类的实现matlab代码，附上具体图像的处理过程及实现结果(Fuzzy C classification of the realization of matlab code, attached to the specific image processing and implementation results)
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Particle image segmentation and matching subroutines themselves are prepared, Dimensional phononic crystals FDTD method calculation examples band gap, Relief computing classification weight.
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关于matlab图像处理 识别 分类 神经网络 支持向量机(About MATLAB image processing, recognition, classification)
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用于图像分类的Matlab代码，简单实用。2017版本(The Matlab code for image classification is simple and practical. 2017 version)
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谷物作为主要粮食和饲料作物,在农业生产中占有重要地位。提高谷物产量和质量的主要方法是选育出优质品种,而在选育品种过程中,对种子的计数是不可缺少的内容。目前,种子的计数方法通常采用人工计数,或半自动的光电计数器,很显然传统的计数方法存在着效率低、准确性不高等缺点。笔者利用计算机图像识别和处理技术实现考种过程中的计数,为谷物粒群的识别、精选、分级等的进一步研究奠定必要的理论与实践基础,并为育种工作提供一种高效、快捷的谷物计数新技术
用Matlab实现这种方法，既能分步对谷物颗粒图像预处理算
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RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and
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使用matlab语言实现图像分类，入门级。(using the language of matlab to making Image classification)
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在matlab中，运用随机森林算法来解决图像特征处理的问题。(In Matlab,the random forest method is used to solve the classification of image features.)
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检测并提取图像的SIFT特征，用于图像识别和分类(Identify and extract the SIFT feature points in the image for image recognition and classification)
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基于稀疏表示的高光谱图像分类的Fisher字典学习方法matlab代码(Hypersynthetic image classification based on sparse representation in Fisher dictionary learning matlab code.)
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用于高光谱图像处理的matlab程序，包括图像融合，降维和图像的极大似然分类程序(Matlab program for hyperspectral image processing, including image fusion, dimension reduction, and maximum likelihood classification of images)
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基于hog特征的svm的图像分类识别，matlab程序(Image classification and recognition based on hog-svm)
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这是一个标准的深度学习图像分类和目标跟踪的matlab程序，效果好，运行平台为matlab2017b.(This is a standard in-depth learning image classification and target tracking matlab program, good results, running platform for matlab 2017b.)
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