搜索资源列表
pcnn
- 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.
DataRecog
- 用神经网络，实现手写数字0-9的识别，对于相似度小的拒绝识别-Using neural networks, implementation figure 0-9 handwriting recognition, the similarity of small refuse recognition
FusionEvaluation
- 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
yichuansuanfaimageseg
- 遗传算法与BP神经网络结合，可以进行彩色图像和灰度图像的分割。-Genetic algorithm and BP neural networks that can be color images and gray-scale image segmentation.
PatternClassificationenglish
- 模式识别经典书籍。清晰地阐明了模式识别的经典方法和新方法，包括神经网络，随机方法，遗传算法以及机器学习理论。-Pattern Recognition classic books. Spell out the classic pattern recognition methods and new methods, including neural networks, stochastic methods, genetic algorithms and machine learning theory
optical_flow
- 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
WaveandNNprotected
- High Performance Face Recognition Based on Wavelet and Neural Networks
A_Phase-based_Approach_to_the_Estimation_of_the_Op
- 一种基于相位的光流计算方法，该方法不同于以往基于微分的计算方法，而是采用空间滤波器，取得非常好的效果。该结果发表于IEEE Trans. Neural Networks,13(5), 1127--1136. -Gautama, T. and Van Hulle, M.M. (2002). A Phase-based Approach to the Estimation of the Optical Flow Field Using Spatial Filtering, IEEE Tr
analgorithmforextractionandanalysis
- 摘要图像特征的提取是视觉图像识别的重要方法之一，采用细胞神经网络（&’’）并行处理器进行图像特征的提取 具有实时快速的优点。该文将介绍&’’ 并行处理器的基本工作原理及其实现图像特征处理的逻辑组合通用方法，并以 图像的纹理分割与识别为例来说明&’’ 并行处理器应用于视觉图像识别的通用编程方法。-Abstract image feature extraction is a visual image to identify one of the important ways, the use
caiqie
- 步态识别图像的初步裁切，对视频监控提取的图像进行裁切-The structures of the neural networks were designed using a constructive algorithm where the basic idea was to start with a small network,then add hidden units and weights incrementally until a satisfactory solution be foun
ACNproj
- Object tracking using Radial Basis Function Networks(Neural networks). The implementation is done in OpenCV.
OpticalCharacterNeuralNetwork
- 文章和附件代码教你如何使用人工智能的神经网络开发一个简单的光学字符识别(OCR)应用程序，程序可以获得非常高质量的识别率和性能。-Creating Optical Character Recognition (OCR) applications using Neural Networks How the use of neural network can simplify coding of OCR applications.
xiaobo
- 本书全面系统介绍了小波分析的基本理论和最新研究成果，重点介绍小波分析的应用成果，并通过软件实现来检验应用效果。全书分为三篇：第一篇是小波理论，包含8章内容，小波分析的发展历史及文献综述、准备知识、多分辨分析与共轭滤波器、连续小波变换、最佳小波基的构造及算法、二维母小波的构造、框架与样条小波理论、时间----频率分析；第二篇是小波应用，包含12章内容，详细介绍了小波分析在图象压缩、流体力学、工业CT、故障诊断、语音分割、数学物理、地球物理勘探、医学细胞识别、线性系统、神经网络等方面的应用；第三篇是
e-bmp
- 易语言验证码识别，基于神经网络，可自行训练！识别验证码必备！-CAPTCHA easy language, based on neural networks, self-training! Identification verification code necessary!
10
- 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
fdp5final
- Face Detection System 基于Gabor特征提取和人工智能的人脸检测系统源代码 使用步骤： 1. 拷贝所有文件到MATLAB工作目录下(确认已经安装了图像处理工具箱和人工智能工具箱) 2. 找到"main.m"文件 3. 命令行中运行它 4. 点击"Train Network"，等待程序训练好样本 5. 点击"Test on Photos"，选择一个.jpg图片，识别。 6. 等待程序检测出人脸区域
neural-network
- 基于神经网咯的文字识别系统，其中源代码是识别程序的，另一个是矩阵类库的。-Text recognition system based on neural networks, in which source code is the identification procedures, and the other is a matrix class library.
neural-network
- 现代数字图像处理技术提高及应用案例详解(matlab版 3.25 基于脉冲耦合神经网络的图像分割-Modern digital image processing technology and application case explanation (matlab version 3.25 image segmentation based on pulse coupled neural networks
neural-network
- 指出了传统边缘检测算子算法的不足,提出了一种利用基于BP神经网络的数字图像边缘检 测算法,即利用传统边缘检测算子检测出来的图像中像素的灰度的不同比例作为学习训练图像,进行神经网络的学习训练,改变神经网络的结构参数得到神经网络的模型参数,最后给出了BP神经网络实现图像边缘检测的实验研究结果。从实现中可发现,将人们关于边缘特征的先验知识包含在内进行数字图像的边缘检测,能够取得比较好的效果-The paper points out the limitation of the traditional
4-Sinc-kernel--Neural-Networks-
- 4个信号理论的支持向量分类方法从内核神经网络以后22(1)49-57 2009 _nelson_-4 A signal theory approach to support vector classification the Sinc kernel Neural Networks 22 (1) 49-57 2009_nelson_nn