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bp神经网络的车辆分类
- c语言编写的基于BP神经网络的对图像车辆分类，其中图像特征提取是用图像不变矩，给出了图像不变矩的样本数据和验证数据。-based BP neural network image of the vehicle classification, Feature Extraction which is the same image moments, the image is unchanged Moments sample data and test data.
Character_Recognition_Using_Neural_Networks
- Character Recognition Using Neural Networks Steps to use this GUI. 1. Open the GUI figure, run it. (accept the matlab to change its directory to new location where the file is stored) 2. First we need to teach Character to computer. For this ty
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.
Researchontheshapefeatureextractionandrecognition.
- 主分量分析(PCA ) 是统计学中分析数据的一种有效的方法, 可以将数据从高维数据空间变换到低维特征空间, 因而 可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中, 用PCA 法提取图像的形状特征, 能够较好地满足识别 层的输入要求。在识别层研究了3 种识别方法: 最近邻法则、BP 网络及协同神经网络方法, 均取得了满意的实验效果。-Principal component analysis (PCA) is a statistical analysis of data in a
ebp4
- BP神经网络例子，主要用于图像处理以及数据挖掘-Examples of BP neural network, mainly for image processing and data mining
Character_Recognition_Training__NN_for_classificat
- 图像特征识别通过神经网络训练方法实现，是学习参考的好资料-you will need first to run the file that name "charGUI4.fig" and on the right side there is a load training set where you have to train the system first, run any data that is should be from 1 to 9 and 0 like ( 1 2 3 4 5 5
bbb
- 人脸识别是近年来模式识别、图像处理、机器视 觉、神经网络以及认知科学等领域研究的热点课题之 一。作为生物特征识别的一个重要方面, 人脸识别在 档案管理系统、安全验证系统、信用卡验证、公安系统 的罪犯身份识别、银行和海关的监控、人机交互等领域 具有广阔的应用前景。与指纹识别、视网膜识别、虹膜 识别等技术相比, 人脸识别技术在数据采集方面手续 比较简单, 使用者更容易接受。-Face recognition in recent years, pattern recogni
Self-organizing_neural_network
- 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-Self-organizing neural network-based data and image processing, image segmentation applied in a very
matlab_shibie
- 基于神经网络的图像识别的基本原理。基于图像像素数据的神经网络识别技术，是用高维的原始图像数据作为神经网络的训练样本。-Based on neural network image recognition of the basic principles. Image pixel data based on neural network identification technology is the use of high-dimensional raw image data as a neural
NN_Recognition
- 1、输入80乘80的英文手写字母图像，对训练数据进行训练，然后输入测试数据，完成字母识别。 2、txt文档详细说明如何配置、运行，一般情况下可以直接运行成功。 3、主要原理采用神经网络进行手写字母识别，准确率较高。 -1, enter 80 x 80 handwritten English alphabet image, the training data for training, and then enter the test data, complete the letter
classification
- 基于分类树的分类，与神经网络相比算法简单，分类结果看数据大小和样本集而定。简单易行的图像处理，对于初学者非常实用。 -Classification tree based on comparison with the neural network algorithm is simple, look at the data classification and sample size may be set. Simple image processing, very useful for beg
GASeg
- 基于遗传神经网络的图像分割算法，包含有测试数据和图像，效果不错-Image segmentation algorithm based on genetic neural network, contains test data and images, good results ~~~
adaboost-and-rbf
- 随机森林算法在图像特征分类回归中的应用，通过结合神经网络进行更好的特征数据处理-Application of random forest algorithm in image classification and regression, better features by combining neural networks data processing
FaceRecognition_CNN(olivettifaces)
- Python实现的基于卷积神经网络的人脸识别测试程序，包含了实验所需的图片数据。-Python implementation of the neural network based on the convolution of the face recognition test procedures, including the required image data.
cnn
- 用于图像分类的源代码，深度学习的应用，cnn卷积神经网络的使用，可以自己更换数据集或者调优，适合初学者使用！-For image classification of the source code, the application of in-depth learning, cnn convolutional neural network, you can replace the data set or tuning, suitable for beginners!
BP-picture
- BP神经网络实现图像压缩，内含源文件和数据，希望可以帮到大家-BP neural network image compression, including source files and data, I hope you can help
Saliency-Detection
- 提出一种新的显着性检测方法，通过将区域级显着性估计和像素级显着性预测与CNN（表示为CRPSD）相结合。对于像素级显着性预测，通过修改VGGNet体系结构来执行完全卷积神经网络（称为像素级CNN）以执行多尺度特征学习，基于该学习进行图像到图像预测以完成像素级显着性检测。对于区域级显着性估计，首先设计基于自适应超像素的区域生成技术以将图像分割成区域，基于该区域通过使用CNN模型（称为区域级CNN）来估计区域级显着性。通过使用另一CNN（称为融合CNN）融合像素级和区域级显着性以形成nal显着图，并
gfmuh
- ECG data and includes source code written in MATLAB, The entire training process BP neural network, Convolution operation is intended to signal and image rendering.