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Description: 一种基于改进径向基神经网络的人脸图像识别方法-RBFNN the Face Image Recognition
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Size: 231944 |
Author: 李豫捷 |
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Description: 采用径向基函数进行图像修复的VC++源代码，用户可交互式地选择破损修复区域。-RBF used for image restoration VC source code, users can interactively choose to repair damaged region.
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Size: 1050624 |
Author: 屈磊 |
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Description: 一种基于改进径向基神经网络的人脸图像识别方法-RBFNN the Face Image Recognition
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Size: 231424 |
Author: 李豫捷 |
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Description: 一个用于MRI和CT图像检索的程序，使用了SVM分类算法和AdaptBoost自适应增强算法。-for an MRI and CT image retrieval procedures, the use of SVM classification algorithm and AdaptBoost adaptive enhancement algorithms.
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Size: 15691776 |
Author: chenxin |
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Description: 用RBF实现的目标图象识别程序,C实现,可以应用于DSP系统.-RBF realize the goal of using the image recognition program, C realize, can be used in DSP systems.
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Size: 352256 |
Author: 安平 |
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Description: 用dsp实现的的小波神经网络进行图象识别编程-Dsp achieved using the wavelet neural network image recognition programming
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Size: 559104 |
Author: 安平 |
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Description: 一个简单的使用IDW和RBF算法对图像（只支持bmp格式）进行变形的MFC程序，可以当作图像处理入门时的练习参考。-A simple algorithm using the IDW and RBF image (bmp format only) to the deformation of the MFC process, image processing can be used as entry to practice at the time of reference.
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Size: 78848 |
Author: maxint |
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Description: 添加CDib类，用IDW算法和RBF算法实现ImageWarping-Add CDib categories, with IDW algorithm and RBF algorithm ImageWarping
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Size: 78848 |
Author: huiwang |
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Description: matlab图像处理工具相，使用了主成分分析，ANN，SVM等方法。-This toolBox used in the image processing(feature extraction and classification)
PCA,LDA,ICA,DCT,RBF,RBE,GRNN,KNN,minimum distance,SVM, and others
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Size: 74752 |
Author: 大长今 |
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Description: 关于rbf神经网络实现图像分类的IEEE英文文献 和大家一起分享-Image Classification using a Module RBF Neural Network
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Size: 163840 |
Author: sfes |
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Description: it is a image recognition with rbf neural network
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Size: 1024 |
Author: parisa |
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Description: 由发展蓝图和RBF监督神经网络的图像分类 希望大家喜欢-Supervised image classification by MLP and RBF neural networks
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Size: 501760 |
Author: dss |
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Description: 基于RBF人工神经网络的遥感图像校正算法pdf-Based on RBF neural network for remote sensing image correction algorithm pdf
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Size: 297984 |
Author: xixi |
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Description: 用IDW和RBF方法实现的Image Warping。没有用到OpenCV。内含DIB类-Image Warping Using IDW and RBF Mathod
No use OpenCV
Include DIB Class
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Size: 721920 |
Author: |
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Description: MATLAB CODE FOR IMAGE CLASSIFICATION USING RBF NETWORK
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Size: 207872 |
Author: parmalik kumar |
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Description: 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 learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.)
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Size: 5120 |
Author: gahuan
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Description: 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 learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.)
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Size: 47104 |
Author: 哼哼1214
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Description: 该文件是用RBF神经网络算法对图像进行处理的一个很好的借鉴的文章(The file is a good reference to the image processing with the RBF neural network algorithm.)
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Size: 2748416 |
Author: 顾炎武 |
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Description: 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。
简单说明一下为什么RBF网络学习收敛得比较快。当网络的一个或多个可调参数（权值或阈值）对任何一个输出都有影响时，这样的网络称为全局逼近网络。由于对于每次输入，网络上的每一个权值都要调整，从而导致全局逼近网络的学习速度很慢。BP网络就是一个典型的例子。(RBF network can approximate arbitrary non-linear functions, can deal with the laws that are difficult to analyse in the system, has good generalization ability, and has very fast learning.
The convergence rate has been successfully applied to non-linear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing and system construction.
Modeling, control and fault diagnosis.
Simply explain why RBF network learning converges faster. When one or more adjustable parameters (weights or thresholds) of the network are applied to any output
When there is an impact, such a network is called a global approximation network. For each input, each weight on the network has to be adjusted, which leads to global approximation.
The learning speed of the network is very slow. BP network is a typical example.
If only a few connection weights affect the output for a local area of the input space,)
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Size: 2573312 |
Author: shunzi1999 |
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Description: 基于RBF的手写数字图像识别，matlab程序，欢迎下载交流(Based on RBF handwritten digital image recognition, matlab program, welcome to download and exchange)
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Size: 216064 |
Author: 戛剑生 |
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