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基于神经网络的图像识别程序
- 基于神经网络的识别程序,程序采用三层BP网络训练,采用了普通定义中加入动量因子的训练法,精确度很高。-based on neural network identification procedures, procedures adopted a three-tier network training BP, with its definition of momentum into the training factor, a high degree of precision.
image_identify
- 实现图像的预处理,包括灰度值转换,二值化,梯度锐化,去离散噪声,整体倾斜调整,字符分割,尺寸归一,紧缩重排等功能,经过神经网络训练后可以字符识别。-image preprocessing, including gray-scale conversion value, the value of the gradient sharpening to discrete noise, overall tilt adjustment, character segmentation, to a size a
gaborandnetwork
- 一个人脸识别程序,包括gabor滤波和用神经网络进行训练
bpnet
- BP神经网络训练代码,可以完成以一般的神经网络训练,输入样本后,可以显示训练结果,采用VC实现,编译后可以直接运行。
chap11
- 采用神经网络对字符进行识别,经多次训练网络可以有较好的识别率
imagevectorquantization
- 本代码是利用matlab开发环境,对图像进行矢量量化,从而实现对图像的压缩;并介绍了需要用到的一些matlab现有函数及其使用方法和功能;在码书的训练方法上选择的是自组织映射神经网络,解码重建后的图像质量较好-The application of Self-Orgnization Feature Maps neural network in image vector quantization
BP
- 利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入,与对应的灰度图对网络进行训练。-The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network trainin
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
face-identification
- 运用神经网络识别简单人脸图形。包括图形处理,训练样本,以及最后识别。-The use of neural networks recognize simple face graphics. Including the graphics processing, training samples, and the final identification.
Particle-swarm-optimization
- 微粒群优化算法(Particle Swarm Optimization,PSO算法)源于鸟群和鱼群群体运 动行为的研究,是一种新的群体智能优化算法,是演化计算领域中的一个新的分支。它 的主要特点是原理简单、参数少、收敛速度较快,所需领域知识少。该算法的出现引起 了学者们极大的关注,已在函数优化、神经网络训练、组合优化、机器人路径规划等领 域获得了广泛应用,并取得了较好的效果。尽管粒子群优化算法发展近十年,但无论是 理论分析还是实践应用都尚未成熟,有大量的问题值得研究。 -
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!
tuxiangfenxi
- 在matlab中对大量的轴承故障的特征信号进行小波包分解,提取特征值,并建立神经网络训练,最终可由网络进行故障的分析-In matlab large number of bearing fault characteristic signal wavelet packet decomposition, extract characteristic values, and the establishment of neural network training, and ultimately by
bp-netual-net
- 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
Handwritten-numeral-recognition
- 联机手写数字识别 数字通过模拟手写板输入,进行特征提取,发现新特征就通过模板保存起来,通过自带的模板进行神经网络训练,可以进行手写数字识别-On-line handwritten numeral recognition
NN.tar
- 神经网络训练算法,加速算法,有很大改进,建立参考。-Recent years have seen a surge of interest in multilayer neural networks fueled by their successful applications in numerous image processing and computer vision tasks. In this article, we describe a C++ implementation of th
BPimage
- 本程序是自己初步设计的BP拟合图像曲面的训练程序,还有诸多不完善之处,请批评指正(This procedure is their own preliminary design of the BP fitting image surface training procedures, there are many imperfections, please criticism correct)
SRCNN_TEST
- 基于卷积神经网络的图像超分辨率重建,不含训练程序,包含已训练好的model !(Test code for Super-Resolution Convolutional Neural Networks (SRCNN))
Untitled2
- BP神经网络基本原理概述:这种网络模型利用误差反向传播训练算法模型,能够很好地解决多层网络中隐含层神经元连接权值系数的学习问题,它的特点是信号前向传播、误差反向传播,简称BP(Back Propagation)神经网络。BP学习算法的基本原理是梯度最快下降法,即通过调整权值使网络总误差最小,在信号前向传播阶段,输入信号经输入层处理再经隐含层处理最后传向输出层处理;在误差反向传播阶段,将输出层输出的信号值与期望输出信号值比较得到误差,若误差较大则把误差信号传回隐含层直至输入层,在各层神经元中使用
CNN
- 完整的CNN卷积神经网络创建、训练及测试。(Complete CNN convolution neural network is created, trained and tested.)
图像扭曲变换
- 图像扭曲变换,用于深度神经网络训练时样本扩增