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math_recognition
- 手写数字识别之模板匹配法，即位图的读写、细化算法、模板的建立以及如何进行批处理识别。-Handwritten numeral recognition of the template matching method, came to the throne map reading and writing, thinning algorithm, template creation, as well as how to identify th
2143-anqn
- 数字识别vc++实现的手写数字识别算法，给做图像处理的朋友一个参考。该程序能识别-noWith vc++ Realize the handwritten numeral recognition algorithms, image processing to make friends as a reference. The program can identify 0 ~ 9 of 10 digits.
NumberRecognition
- 此程序用于识别手写数字，主要是采用基于特征的方法，用一个5×5的栅格将数字分成25分，每份为一个特征，共有25个特征，然后进行特征匹配，识别出数字。-This procedure used to identify handwritten digits, mainly based on the characteristics of the method, using a 5 × 5 grid will be divided into 25
ES203
- 使用matlab提供的bp网络工具实现手写数字识别。内涵大量测试用手写数字-Bp using matlab network tools available to achieve handwritten numeral recognition. Test a large number of handwritten digital content
nnpractice
- 神经网络手写数字识别。配合美国MNIST标准手写数字字体库-Handwritten digit recognition neural network. With the U.S. standard of handwritten digital font library MNIST
num
- 利用matlab采用基于Gabor特征的识别算法实现手写数字识别-Using matlab recognition based on Gabor feature recognition algorithm for handwritten numeral
bp
- BP神经网络的手写数字识别 识别数字为0~-BP neural network recognition of handwritten numeral recognition numbers from 0 to 99
readMNIST
- 用ELM实现手写数字的识别，快速，用MNIST数据库(Handwritten numbers recognition realized by ELM)
kmean
- 通过编写Kmeans算法识别自己的手写数字0——9个数字(Through the preparation of Kmeans algorithm to identify their handwritten numbers 0 - 9 numbers)
实验45 手写识别实验
- 基于STM32的手写识别，使用STM32战舰V3开发板，STM32F3ZET6。在LCD触摸屏幕中，滑动手指，可以识别手写的字符和数字。(STM32-based handwriting recognition, the use of STM32 warship V3 development board, STM32F3ZET6. In the LCD touch screen, slide your finger to recogniz
MNIST
- MNIST手写体数字识别库及图片提取代码MNIST手写数字库识别实现摘要手写数字识别是模式识别的应用之一。文中介绍了手写数字的一些主要特征,并提出了截断次数特征并利用截断次数特征进行了实验(MNIST handwritten digital identification library and picture extraction code MNIST handwritten numeral library identification
neuralnetwork-sample
- 由java编写的，具有gui界面的，手写数字识别神经网络示例(Written by Java, with GUI interface, handwritten numeral recognition neural network examples)
train-labels-idx1-ubyte
- 用于手写数字识别的训练数据（标签） 数据格式：前32位为2049，再32位为数据数量，之后每一位都是标签值(Training data (tags) for handwritten digit recognition)
t10k-labels-idx1-ubyte
- 用于手写数字识别的预测数据（标签） 数据格式：前32位为2049，再32位为数据数量，之后每一位都是标签值(Predictive data (tags) for handwritten numeral recognition)
train-images-idx3-ubyte
- 用于手写数字识别的训练数据（图片） 数据格式：前32位为2049，再32位为数据数量，再32位为图片宽度M，再32位为图片高度N，之后每N*M位都是图片的像素值(Training data (pictures) for handwritten digit recognition)
t10k-images-idx3-ubyte
- 用于手写数字识别的预测数据（图片） 数据格式：前32位为2049，再32位为数据数量，再32位为图片宽度M，再32位为图片高度N，之后每N*M位都是图片的像素值(Predictive data (pictures) for handwritten numeral recognition)
kNN
- KNN算法改进约会网站配对效果；KNN实现手写数字识别(KNN algorithm to improve the matching effect of dating sites; KNN handwritten numeral recognition)
BP神经网络实现手写数字识别matlab实现
- BP神经网络实现手写数字识别matlab实现(Matlab implementation of handwritten digit recognition based on BP neural network)
手写数字识别
- 一个练习机器学习的算法，解决手写数字识别的算法(An algorithm that exercises machine learning to solve the handwritten numeral recognition algorithm)
mnist1
- 训练手写数字识别算法，正确率达到91.6%(Training handwritten numeral recognition)