搜索资源列表
Hand_num
- 基于神经网络及GUI触摸板的手写数字识别,基本的机器学习例子(Handwritten numerals recognition based on neural network and GUI touch board, basic machine learning examples)
xlrd-1.1.0.tar
- 手写字体识别数据专用集,可以用来测试神经网络,深度血虚(Handwritten font recognition data set)
程序
- 模式识别课程,相关实验的手写字符识别代码。(Pattern recognition course, handwritten character recognition in related experiments)
my_cnn.tar
- 用卷积神经网络实现手写数字识别,数据集为mnist数据集(Convolution neural network is used to realize handwritten numeral recognition. Data set is MNIST data set.)
基于SVM的手写字体识别
- 基于SVM的手写字体识别,含有源程序和数据,可直接运行(SVM Based Handwriting Recognition)
tensorboard
- tensorflow手写数字识别,提高识别的准确率(Tensorflow handwritten numeral recognition, improve the accuracy of recognition.)
sc
- 手写数字签名识别源代码使用matlab编写(Handwritten digital signature recognition source code, written in MATLAB.)
基于MATLAB的文字识别
- 基于matlab的手写字体识别程序,并对结果进行保存(Matlab based handwritten font recognition program, and save the results.)
simpleCNN
- 在anaconda+opencv+tensorflow平台下,利用简单的CNN卷积神经网络进行手写字符识别(Under the anaconda+opencv+tensorflow platform, we use simple CNN convolution neural network to handwritten character recognition.)
cnn
- 手写数字识别的简单实现,CNN入门到深入,三个版本供读者使用。(Simple Implementation of Handwritten Number Recognition, Getting Started with CNN)
手写数字识别
- 通过训练图片中数字0~9,跟着通过手写输入识别出所写数字的类别。(By training the number of 0~9 in the picture, we can identify the category of the written number followed by handwritten input.)
基于libsvm的手写字体识别
- 对于0到9这十个手写体数字进行识别,针对不同字形的手写体数字进行预处理(For 0 to 9, the handwritten Numbers are identified, and the handwritten Numbers of different glyphs are pretreated.)
R语言 svm 手写数字识别
- 用R语言写的手写数字识别算法(svm 方法)(Handwritten numeral recognition algorithm written in R language (SVM method))
CNN
- 手写数字识别的数据集 matlab实现cnn(Data Set for Handwritten Number Recognition Realization of CNN in matlab)
手写数字识别
- 运用卷积神经网络进行特征提取,然后进行分类(Using convolution neural network to extract features and classify them)
DNN实现手写数字识别
- DNN实现手写数字的识别,准确率80以上,可以自行改变学习率等,希望能帮助到大家。
1111
- 基于PCA的手写数字识别源码,内附有说明文件,非常清晰!运行环境:matlab。(Handwritten digital character recognition based on PCA and BP network)
BP_mnist_UI-master
- 基于BP神经网络的手写数字识别,有完整代码(based image segmentation algorithm)
基于深度学习的手写数字体识别
- 基于深度学习的手写数字体识别,以卷积神经网络(CNN)作为网络模型,利用mnist手写数字训练数据集训练手写数字识别模型,搭建手写数字识别系统,并用自己手写的数字照片进行测试。
深度学习CNN手写数字识别
- 利用CNN网络手写数字识别,注释清楚,损失函数用的是focalloss,标注明确,可以跑通,框架是pytorch