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mclassex4
- zip code handwriting detection by matlab
bprecognition
- 采用神经网络实现手写识别的一种方法，建立Bp神经网络，采用快速训练方法，可快速完成一类相关手写字体的模式识别，识别率较高，当字体变化较大识别率降低时，可重新训练具有较强的适应性。实验证实本方法较好实现了手写字符识别，但也存在识别速度较慢，有时训练不收敛等缺点-Handwriting recognition using neural network is a way to establish Bp neural network, using fast training methods, and c
bayesclassifier0
- bayes分类器，脱机手写识别，含实验数据-bayes classifier, off-line handwriting recognition, with the experimental data
hmm
- Handwriting recognition with hmm!
code
- Handwriting recognition with template
svm
- Handwriting recognition with svm
ThreeBp
- 三层bp网络实现三种模式识别，没有使用matlab工具箱，完全自己手写-Three modes of three bp networks to identify, do not use matlab toolbox, completely on my own handwriting
miu_for_CMA
- CMA_4QM算法，本人自己手写的关于CMA的算法，结构很清晰，有注释说明，对初学者有很大的参考价值-CMA_4QM algorithm, my own handwriting on the CMA algorithm, the structure is very clear, there are explanatory notes for a great reference for beginners
10mcmb26
- Handwriting recognition technology using matlab
numbercheck
- 检测手写输入,有几种方法，例如贝叶斯方法，几何方法等等。-Handwriting Detection
HandWeitenNumRecognition
- 通过学习BP神经网络技术，对手写数字进行识别，基于结构的识别法及模板匹配法来提高识别率。-Through the study of BP neural network technology, digital handwriting identification, structure-based identification method and template matching method to improve the recognition rate.
GIUandDIP
- GIU的综合应用，其中包括建立简单的GIU以及按键滑条等使用和图像处理的例子，包括图像的伽马变换，幂次变换，放大缩小旋转，各种高通低通滤波器（理想，高斯，巴特沃斯），通道变换等。（纯自己手写！！）-GIU comprehensive application, including the establishment of a simple GIU and slider buttons and other examples of the use and image processing, inclu
handwriting
- 手写体识别系统，用于对0-9的数字识别出正确率-Handwriting recognition system, for 0-9 identify the correct rate
chapter19
- 基于SVM的手写字体识别,简单介绍SVM的应用-SVM handwriting recognition based applications briefly SVM
数字识别
- 手写体识别，包括样本，基于传统神经网络编写，使用MATLAB神经网络工具箱(Handwriting Recognition)
Lenetchange
- 卷积神经网络CNN，基于手写体数据库的相关训练(Convolution neural network, handwriting training)