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DL : 0
遗传算法(图像处理)-genetic algorithm (image processing)
Date : Size : 62kb User : 丁建军

这是图象处理模式识别一书的源代码,包括C++和MATLAB的程序,对于做这方面的研究人员来说,会很有帮助的。-This is an image processing pattern recognition on the source code, including C and Matlab procedures for doing this kind of research personnel, will be very helpful.
Date : Size : 1.74mb User : 丽云

对于含有噪声的的数字图像模式“1、2、3、4”,使用“hopfield”神经网络,进行联想、识别,以去除噪声的影响。-for containing noise of the digital image model "1,2,3,4", "hopfield" neural network, Lenovo, identification, in order to remove noise impact.
Date : Size : 2kb User : 潘盼

IRIS数据 用于聚类方法 主要用于模式识别、图像分割等-IRIS data for clustering method used pattern recognition, image segmentation, etc.
Date : Size : 4kb User : 王超

MODEL-BASED FINITE MIXTURES USING THE EM ALGORITHM的matlab实现-MODEL-BASED FINITE MIXTURES USING THE EM A the Matlab achieve LGORITHM
Date : Size : 2kb User : 黄风

尿沉渣图像识别,采用形态学图像分割,som进行识别!-urine image recognition, image segmentation using morphological, som identification!
Date : Size : 2kb User : 李明

DL : 1
人脸定位的MATLAB源程序,希望对做图象处理的同志有帮助。-Face positioning MATLAB source, and I hope to do the image processing to help comrades.
Date : Size : 626kb User :

这是一些有关《神经网络模式识别及其实现》的源程序 比较经典,有很大的参考价值-This the "pattern recognition and neural network to achieve" classic comparison of the source, a great reference value
Date : Size : 553kb User : 小熊

中心点漂移是一种非监督聚类算法(与k-means算法相似,但应用范围更广些),可用于图像分割,基于Matlab实现的源码。 MedoidShift is a unsupervised clustering algorithm(similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code.-Center drift is a non-supervised clustering algorithm (k-means algorithm with the similar, but more a wider range of applications), can be used for image segmentation, based on the realization of the source Matlab. MedoidShift is a unsupervised clustering algorithm (similar to k-means algorithm, but can be used in border application fields), can be used for image segmentation. Included is the Matlab implementation source code.
Date : Size : 36kb User : 陈明

DL : 0
matlab 关于二值图像熵和交叉熵的计算程序,这一程序与结合其它方法对图像进行分割,作为一个判断标准.-matlab on the binary image entropy and cross entropy calculation procedure, which in combination with other methods and image segmentation, as a criterion.
Date : Size : 1kb User : 张永康

根据神经网络的算法对三幅训练图像和测试图像进行识别。-According to neural network training algorithm for three test images and image recognition.
Date : Size : 43kb User : xjzhang101

DL : 0
利用改进的脉冲神经网络完成灰度图像的分割-The use of impulsive neural networks to improve the completion of gray-scale image segmentation
Date : Size : 1kb User : 岳碧波

DL : 0
该源码是神经网络中常用的遗传算法的代码。遗传算法是最优化常用的解法之一。-The source code is generated gabor operator of the source image characteristics, such as image segmentation can be used.
Date : Size : 2kb User : xiao

DL : 0
图像纹理提取,这是用matlab编的图像纹理提取程序,该方法能有效的用于纹理分析。-Image texture extraction, which is compiled using matlab image texture extraction process, the method can be effectively used for texture analysis.
Date : Size : 1kb User : liulili

用matlab实现算法,基于遗传算法的图像分割问题-Matlab algorithm based on genetic algorithm, the image segmentation problem
Date : Size : 346kb User : 加仑

DL : 0
MR图像分割的博士论文,对医学图像处理尤其是医学图像分割很有帮助-MR image segmentation of the doctoral thesis, especially in medical image processing medical image segmentation helpful
Date : Size : 7.97mb User : 陈媛媛

利用大量图像数据对卷积神经网络算法进行训练,通过卷积、池化、下采样以及全连接层训练后的卷积神经网络在图像识别精度越来越高。(By using a large number of image data to train the convolutional neural network algorithm, the accuracy of the image recognition is higher and higher by convolution, pooling, down sampling and full connection layer training.)
Date : Size : 3kb User : aperture

DL : 0
High simulation efficiency, Modeling and simulation pwm rectifier In the MATLAB image texture feature.
Date : Size : 4kb User : tougaofao

Object_Removal_by_Exemplar-Based_Inpainting matlab version
Date : Size : 8kb User : 不开窍的娃

图像重建反投影、滤波反投影仿真,如果有需要的话,可以详细我的。(Image reconstruction backprojection and filtering back projection simulation)
Date : Size : 9kb User : 强哥@you
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