搜索资源列表
BP network.matlab平台的基于bp神经网络的遥感图像分类
- matlab平台的基于bp神经网络的遥感图像分类,matlab platform bp neural network-based remote sensing image classification
pcnn的matlab实现
- pcnn的matlab实现，pcnn神经网络主要用于图像去噪分割等,the realization of the matlab PCNN, pcnn neural network used mainly for segmentation, such as image denoising
matlab(BP).rar
- BP神经网络，可以处理图像进行分类等各种处理的源码,BP neural network image processing source code
matlab.rar
- MATLAB 神经网络用于数字识别源程序 手写数字识别，有图例，大家可以看看,MATLAB neural network to identify the source for digital handwritten numeral recognition, there are legends, we will look at
matlab.rar
- 人工神经网络用于图像分割的matlab程序代码，此程序分割的是车牌图像,Artificial neural network for image segmentation matlab code, this procedure is the license plate image segmentation
MATLAB.rar
- 基于自组织神经网络数据及图像处理，在图像分割中应用极强。很好的源程序。 ,Self-organizing neural network-based data and image processing, image segmentation in the application of highly. Very good source.
Markov-Decision-Process-matlab
- 马氏过程的应用很广， 机器人路径计划， 自动飞行器导航，多目标跟踪， 电梯计划， 网络交换和路由， 银行客户保有等等。-Application of Markov process is broad, robot path plan, automatic vehicle navigation, multi-target tracking, lift plans, network switching and routing, bank customers to maintain and so on.
shuzishibie(matlab)
- 本程序能实现离线的数字识别，在MATLAB下运行，同时可以用其中部分代码实现图像的灰度，二值化，细化，归一化等功能，采用Bp神经网络。-This procedure can achieve the number of off-line identification, in the MATLAB run, at the same time part of the code can achieve one of the gray-scale images, binarization, thinnin
Neural-Network-pattern-recognition
- bp人工神经网络模式识别教程示例，研究人脸识别 手势识别有帮助-bp nervel network trainning and recognition ,e.g:face & dynamic hand gesture detection and face recognition .I hope it would be very useful for researcher !
wnn_forcast
- 用小波神经网络变换对时间序列信号进行预测，并做了测试，效果很好，请参考-Transform using wavelet neural network to predict the time series signal, and do a test with good results, please refer to
ann
- matlab入门教程简单与详细版本、matlab神经网络源程序工具箱 、turbo码的c语言和matlab仿真程序 加州大学一博士写的基于sift的图像匹配源代码,.rar-matlab simple and detailed version of the Getting Started tutorial, matlab neural network toolbox source code, turbo codes in c language and matlab simulation prog
shibie
- 实现车牌的自动识别、分割和神经网络处理。-To achieve the automatic license plate recognition, segmentation and neural network processing.
chapter4
- 《数字图像处理与机器视觉:Visual C++与Matlab实现》4 特征提取,图像识别初步,人工神经网络,基于ANN的数字字符识别系统-" Digital image processing and machine vision: Visual C++ and Matlab to achieve" four feature extraction, image recognition initially, artificial neural network, ANN base
LicensePlateCharacterRecognitionWholeProcedure
- 一个关于车牌识别的完整程序，字符识别部分用的是神经网络的相关知识-A complete program of license plate recognition, character recognition part of the neural network with the knowledge
shuohuarenshibie-MATLAB-duandianjiance-yujiazhong-
- 说话人识别代码,端点检测,预加重,MFCC..采用的模型是神经网络~-Speaker identification code, endpoint detection, pre-emphasis, MFCC .. neural network model is adopted ~
213
- Matlab在图像处理与目标识别方面的应用实验程序示例。包括三个程序以及详细文档：一、染色体识别与统计，二、汽车牌照定位与字符识别，三、基于BP神经网络识别字符的简单实验-Matlab image processing and target recognition in the application of experimental procedures for example. Consists of three procedures, and detailed documentation:
yuanchuang1
- 车牌识别的一个完整程序，其中定位方式用的是形态学办法，识别部分是神经网络，程序比较简单，但能实现系统识别要求，并有数个图片示例支撑，适用于初学者弄懂程序，学习思维方法。-License Plate Recognition of a complete program, including positioning the morphological approach used to identify parts of a neural network, the program is relative
License-Plate-Recognition
- 基于神经网络的车牌识别matlab源码,利用给定的车牌图像库中（在指定的文件夹之中），任意选择其中的多副车牌图像，对其中包含的数字（0～9）或英文字符（A～F）进行手工提取训练。-License plate recognition based on neural network matlab source code, the use of a given license plate image library (among the specified folder), choose one of
bpandkohonen
- 神经网络源码，可应用于遥感图像的分类，采用的包括bp、kohonen。可以作为范例来学习。-Neural network source code can be used in remote sensing image classification, using the included bp, kohonen. Can serve as examples to learn.
LPR-neural-network
- 这是我自己做的一个基于神经网络的车牌识别程序，主要针对的是国内的蓝底车牌，希望对大家有帮助！-This is my own doing a neural network-based license plate recognition program, mainly for the domestic blue license plates, we want to help!