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用神经网络进行手写字母识别(java程序下载).zip
- 用神经网络进行手写字母识别(java程序下载)
手写数字识别之Fisher线性判别
- 手写数字识别之Fisher线性判别-handwritten figures identifiable Fisher Linear Discriminant
Handwrittennumeralrecognition
- 手写数字识别算法，基于置信度分析和多信息融合的手写数字识别。-Handwritten numeral recognition algorithm, based on the confidence level and multi-information fusion analysis of handwritten numeral recognition.
shibie
- 针对10个手写数字的识别问题，设计了一个BP神经网络，使它能够正确识别10个数字。-Against the 10 handwritten numeral recognition problem, a BP neural network is designed so that it can correctly identify the 10 digits.
ANNRecognizer
- C#编写的BP神经网络模型的手写识别器，可以识别数字-C# prepared by the BP neural network model of the handwriting recognizer, you can identify the numbers
BPHandIdentifyRate
- 基于bp神经网络的手写识别系统 matlab仿真-Bp neural network-based handwriting recognition system simulation matlab
tablet-delphi
- 一个简单的tablet delphi源码，可扩展手写识别等功能-A simple tablet delphi source, scalable features such as handwriting recognition
基于概率神经网络的手写体数字识别
- 基于概率神经网络的手写数字识别，利用概率神经网络识别1-9的手写数字，matlab程序(Handwritten numeral recognition based on probabilistic neural network)
codecnnMNIST
- 用cnn卷积神经网络实现对mnist手写库的识别(mnist classfication with convolution neural network)
stm32手写识别实验
- 可以利用stm32的彩屏进行手写文字的输入，方便快捷。(Can be handwritten text input using the STM32 color screen, convenient and quick.)
手写识别实验
- stm32f4手写设置，运行与测试等，开发平台KEIL,希望对大家有帮助(Stm32f4 handwriting settings, running and testing, development platform KEIL, we want to help)
Character_Recognition
- 本程序主要参照论文，《基于OpenCV的脱机手写字符识别技术》实现了，对于手写阿拉伯数字的识别工作。识别工作分为三大步骤：预处理，特征提取，分类识别。预处理过程主要找到图像的ROI部分子图像并进行大小的归一化处理，特征提取将图像转化为特征向量，分类识别采用k-近邻分类方法进行分类处理，最后根据分类结果完成识别工作。 程序采用Microsoft Visual Studio 2010与OpenCV2.4.4在Windows 7-64位旗舰
handwrite2
- 采用KNN算法，用PYTHON语言实现的手写数字图像识别(Using KNN algorithm, handwritten digital image recognition with PYTHON language)
MNIST
- 简单的手写数字识别，在深度神经网络中的简单尝试，对于初学者有个很好的理解(Simple handwritten numeral recognition, in the depth of neural network simple attempt, for beginners have a good understanding)
数字识别
- python的keras调用theano创建cnn识别minist手写数字(use keras of python to create cnn to recognize digit wrote by hand)
神经网络mnist
- 利用神经网络对手写识别系统进行分类，正确率高达92%。(Using neural network to classify handwritten recognition system, the correct rate is as high as 92%.)
BP神经网络手写数字识别
- 使用bp神经网络算法识别手写阿拉伯数字图像，三层的误差反馈神经网络，可输出准确率，数据集为60000条数据，每条数据是一张28*28的图片(The BP neural network algorithm is used to recognize handwritten Arabia digital images, and the error feedback neural network of three layers can outp
VC++数字、英文字符、汉字及手写识别实例
- 简单的字符识别程序，能实现手写字符、英文、符号的识别，采用了位图以及预处理(character recognition)
手写识别实验
- 基于stm32f103系列芯片开发的人脸识别实现(Realization of Face Recognition Based on STM32F103 Series Chips)
字符识别孪生网络
- 运用孪生网络技术识别minst手写字符集并计算准确率(Identifying Minst Handwritten Character Set and Calculating Accuracy Using Twin Network Technology)