用C＃训练支持向量机进行字符识别 [英] Training a support vector machine in C# for character recognition

问题描述

对于那些刚接触SVM的人来说，如果他们想在C＃中在各自文件夹中分发的不同图像上训练SVM，最好的起点是什么？



这是我们的图像处理课程中的作业。我们在C＃中对图像进行了不同的IP算法，但是，几乎没有教师的帮助，我不知道如何在一堆字符图像上处理C＃中的SVM训练。



我们还没有学过机器学习课程。通过谷歌搜索，我已经掌握了一些SVM的基本知识。但是仍然不知道如何在C＃中实现训练数据。有图书馆吗？据我所知，机器将输出一个培训文件，用于识别图像中的文字。



培训数据如下所示：http：// www .tiikoni.com / tis / view /？id = 6b26c8e



任何帮助表示赞赏。



我尝试过：



尝试了解SVM的基础知识。不知道从哪里开始。

For those new to SVMs, what would be the best place to start if they want to train a SVM in C# on different images of characters distributed in their respective folders?

This is an assignment in our Image Processing course. We have been doing different IP algorithms on images in C# but, with almost no help from instructor, I have no clue how to deal with training SVMs in C# on a bunch of character images.

We haven't studied Machine Learning course yet. And through googling I have gotten some basic knowledge of SVMs. But still have no idea how to implement for training data in C#. Is there any library? As per my knowledge the machine will output a training file that will be used to recognize the text from images.

The training data looks like this: http://www.tiikoni.com/tis/view/?id=6b26c8e

Any help is appreciated.

What I have tried:

Tried understanding the basics of SVM. Not sure where to start.

推荐答案

是的，有SVM库。

Bing搜索libsvm csharp给出超过10,000个结果（如何很多都很有用吗？）。

.NET应用程序中有SVM实现。

我怀疑有使用它们的例子。



如果您真的想了解机器学习和分类系统，请查看在线免费，入门机器学习来自加州理工学院！ [ ^ ]

它不会给你代码，但你会学习很多关于如何自己做的事情！

如果你尝试参加课程，我建议你使用 Octave（一个免费的Matlab兼容系统） [ ^ ] 练习和作业。

SVM 本课程涵盖。

您可能想要在深入研究SVM之前的一些ML背景。有一个原因，它不接近加州理工学院电视的开头！ （我的母校！）

祝你好运。

Yes there are SVM libraries.
Bing search of "libsvm csharp" gives over 10,000 results (how many are useful?).
There are SVM implementations for use in .NET applications.
I suspect there are examples on using them.

If you really want to learn about Machine Learning and Classification systems, check out the Free, introductory Machine Learning online course from Caltech![^]
It won't give you the code, but you'll learn lots about how to do it yourself!
If you try taking the course, I suggest using Octave (a free Matlab-compatible system)[^] for practicing and homework.
SVM is covered in this course.
You probably want some of the ML background before digging into SVM. There's a reason it isn't near the beginning of the telecourse from Caltech! (My alma mater!)
Good luck.

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