搜索资源列表
addline
- ADALINE的字符识别，有图形界面。可以方便使用并了解ADALINE的LMS算法-ADALINE Character Recognition, a graphical interface. Easy to use and understand ADALINE LMS algorithm
extract_yellow_region
- 车牌识别技术422 10.1 系统简介422 10.1.1 车牌定位技术综述423 10.1.2 车牌字符 识别技术综述423 10.2 车牌图像定位与分割算法424 10.2.1 车牌图像的-Vehicle Identification Technology System 422 10.1 422 10.1.1 plates positioning technology on 423 10.1.2 License Plate Recognition Technology 423 10.2 pl
nnd10lc
- Windrow-Hoff学习算法的源程序，实现ADALINE机器的自适应学习，功能用于字符识别，完全界面显示。-Windrow-Hoff learning algorithm source, the realization ADALINE machines adaptive learning, for character recognition function, the interface shows entirely.
offline-character-recognise
- 脱机字符识别算法，包括手写数字识别之Fisher线性判别，手写数字识别之模板匹配法，数字识别之神经网络法，细化算法 -offline character recognition algorithms, including handwritten digital identification Fisher Linear Discriminant. Handwritten identification template matching, digital identification neura
AllNeuralNetworkCompute
- 包含6个*.m文件，分别是adline网络，bp网络，hopfiled网络，字符识别，学习速度自适应，和增强型lms算法的六个仿真算法程序，真是我的珍藏，这次全抖出来了。-contains 6 m *. documents were adline network bp network hopfiled network, character recognition, adaptive learning speed, lms and enhanced algorithm simulation alg
zifushibie
- 基于matlab的免疫算法，并实现字符识别功能
ex3
- 基于BP神经网络识别字符. BP神经网络算法是把一组样本输入输出问题转化为一个非线性优化问题，并通过梯度算法利用迭代运算求解权值的一种学习方法。采用BP网络进行分类，并附加线性感知器来实现单字符的有效识别，算法简便，识别率高，可适用于多种高噪声环境中的印刷体字符识别。-BP neural network based character recognition. BP neural network algorithm is a set of sample input and output is
3
- 基于改进BP算法的数字字符识别，改进原有的BP算法，实现更好的数字字符识别。-BP Algorithm Based on Improved digital character recognition, improving the original BP algorithm, to achieve a better digital character recognition.
NES
- 浅谈人工神经网络；人工神经网络的研究与应用；人工神经网络在图像匹配中的应用；于神经网络算法的字符识别方法研究-Of artificial neural networks artificial neural network research and applications Artificial Neural Network in Image Matching on neural network algorithm for character recognition method
car
- 汽车车牌的图像识别。 根据车牌凸角轮廓特征，采用MPP算法进行车牌倾斜校正；采用彩色图像分割方法，最大限度的去除图像噪声干扰；设计了基于神经网络的多种彩色背景车牌字符识别方法，取得了良好的效果。-Image recognition of vehicle license plates. According to plate convex contour feature, the use of MPP plate tilt correction algorithm using color imag
kecheng2011
- 课程设计要求 0 实验一 基于模板匹配的字符识别 1 实验二 基于C均值算法的车辆检测与跟踪 3 实验三 水果分类系统设计 5 实验四 基于遗传算法的图像歪斜校准 6 实验五 基于BP网络的函数逼近 9 实验六 空调模糊控制系统设计 -Curriculum design requires 0 Experimental one based on template matching character recognition 1 C-means algorithm
6b4770f9-e86b-4957-b4cd-98ad54e51f35
- 分析了hopfiled网络和遗传算法的基本原理，探讨了hopfiled在字符识别中的应用，针对hopfiled存在的弱点，提出了基于遗传算法的hopfiled的字符识别。-The analysis hopfiled network and the basic principle of genetic algorithm, this paper discusses the application of hopfiled in character recognition, aiming at the
LMBP
- 神经网络中的LMBP算法实现字符识别，有详细的注释-The LMBP neural network algorithm for character recognition, there are detailed notes
word-recognition-and-nerual-networks
- 基于卷积神经网络的字符识别技术，较好的算法！！神经网络、-Convolution-based neural network character recognition technology, better algorithm! ! Neural network,
TGF
- 在 Windows 环境中用MATLAB实现LMS学习算法，解决T-G-F字符识别问题。-Windows environment using the MATLAB realize LMS learning algorithm to solve the problem of TGF character recognition.
1
- 实验一：基于LMS算法的“苹果-橘子”分类问题 实验二：基于LMS算法的T-G-F字符识别问题 通过以上两个实验，了解ADALINE网络的结构及计算机制，掌握LMS算法，并会利用该算法来解决简单的模式分类问题。1， 学习ADALINE网络的基本结构及其学习机制，并在Matlab中实现 2， 分别对上述两类分类问题进行实现，并根据实验结果完成实验报告 -Experiment 1: Based on LMS Algorithm Apple- Orange classificati
zifushibie
- 基于神经网络的字符识别。利用神经网络算法在c语言下实现车牌字符的智能识别。-Character recognition based on neural network. Using neural network algorithm to realize the intelligent recognition of license plate characters in C language.
mathcthealphabet
- 一种字符识别算法的matlab实现，带有样本。识别精度较高。-a algorithm of match the alphabet
BP神经网络数字识别（matlab2014a）
- 利用BP神经网络识别易拉罐底字符识别，运行前注意阅读算法说明和代码中相对路径的设置。(The BP neural network is used to identify the character recognition of the bottom of the can, and the pre operation attention to the reading algorithm and the setting of the relative path in the code.)
Python机器视觉编程
- 《Python计算机视觉编程》是计算机视觉编程的实践指南，依赖Python语言讲解了基础理论与算法，并通过大量示例细致分析了对象识别、基于内容的图像搜索、光学字符识别、光流法、跟踪、三维重建、立体成像、增强现实、姿态估计、全景创建、图像分割、降噪、图像分组等技术。另外，书中附带的练习还能让读者巩固并学会应用编程知识。("Python Computer Vision Programming" is a practical guide to computer vision pro