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利用脉冲耦合神经网络（pcnn）实现图像滤波的源程序，已经过测试。-Using pulse coupled neural networks (pcnn) the realization of the source image filtering, has been tested.
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Please run Demo_evaluation.m
This toolbox contains Matlab files that implement the image fusion criteria used in my paper
Qu Xiao-Bo, YAN Jing-Wen, XIAO Hong-Zhi, ZHU Zi-Qian. Image Fusion Algorithm Based on Spatial Frequency-Motivated P
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Phase-based Opic Flow Algorithm, described in
Gautama, T. and Van Hulle, M.M. [2002]. A Phase-based Approach to the
Estimation of the Optical Flow Field Using Spatial Filtering.
IEEE Trans. Neural Networks, 13[5], 1127--1136.- Phase-based
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简单的车牌定位程序 MATLAB环境下对简单的图片很容易定位车牌-license plates have three letters and four numbers,plate images were used in order to train the two neural networks,one for the letters and the other for the numbers
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MATLAB进行图像处理的一些实用程序，有图像增强 ，图像复原的，还有神经网路的，还有一些实例，比如形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象 。内附说明，希望能够对正在进行数字图像处理学习的人有帮助-MATLAB image processing some of the practical procedures, image enhancement, image restoration, as well as neural networks, there are some in
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本文件包含的程序实现了神经网络在遥感正射影像云影检测领域的应用，效果良好。-This document contains procedures for implementation of neural networks in remote sensing cloud shadow detection orthophoto application of the field to good effect.
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国外的一个车牌识别程序，主要是基于颜色特征提取分割的，内置神经网络。-A license plate recognition program abroad, mainly segmentation based on color feature extraction, built-in neural networks.
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主要是用于处理图像，小波分析，神经网络等一系matlab中最常用的一些技术-Mainly used for image processing, wavelet analysis, neural networks, a series of matlab in some of the most commonly used technique
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NETLAB algorithms for PR+书籍代码。学习模式识别的很好的老外书籍。基础模型很多，代码很细致，有很多算法的实现细节，对于应用很有帮助，-chapter covers a group of related pattern recognition techniques and includes a range of examples to show how these techniques can be applied to solve practical problems.
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多层前向反馈式神经网络是目前应用比较广泛的人工神经网络，其中BP(Back Propagation network，简称BP网络)学习算法是最著名的多层前向反馈式神经网络训练算法之一。该算法在图像处理和图像识别领域已经取得令人瞩目的成就，其主要思想是利用已知确定结果的样本模式对网络进行训练，然后利用训练好的网络进行图像的处理或识别。本文将讨论用MATLAB实现BP神经网络对人脸角度的分析。 -Multilayer feedforward neural network feedback is us
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Code for CVPR15 paper Learning to Compare Image Patches via Convolutional Neural Networks
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This package allows researches to apply the described networks to match image patches and extract corresponding patches.
We tried to make the code
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