资源列表
DirectShowzhidao
- DirectShow指南源码,非常好的资料，-DirectShow Source Guide
sorce_code_XieFengYin(image_processing)
- 谢凤英 VisualＣ＋＋ 数字图像处理，关于图像处理比较靠前的源代码-Ｘｉｅ ＦｅｎｇＹｉｎｇ Ｖｉｓｕａｌ Ｃ＋＋ ｉｍａｇｅ ｐｒｏｃｅｓｓｉｎｇ，ａ ｇｏｏｄ ｓｏｕｒｃｅ ｃｏｄｅ
HTTP代理服务器源码
- 基于vc6的http代理服务器源码，功能相对齐全
Visual_CPP_Practical-Guide
- 本书从编程基本概念入手，结合Visual C++编程环境，详细叙述了面向对象的程序设计方法及Visual C++ 6.0集成开发环境的使用。-Starting from the basic concepts of programming book, combined with Visual C++ programming environment, detailing methods of object-oriented programming and Visual C++ 6.0 integra
food
- 完成界面设计的项目,是个相当不错的模板文件，适合刚开始开发网站而没有模板的人-a project which hava benn completed all over
sshzhenghe
- 这个是本人整合的structs+hibernate+spring与大家分享-This is my integration structs+ hibernate+ spring to share with you
kmeans_report
- 数据挖掘kmeans图像聚类实验,用 VC 或 Java 实现 k-means 聚类算法， 分别以迭代次数及分配不再发生变化为算法终止条件，用图片（自己选择）作为数据集，比较运行时间（画出时间与像素点的关系曲线图，因此须用多幅像素个数不同的图片进行实验） 提交实验报告与源代码-Data mining kmeans image clustering experiments, using VC or Java implementation of k-means clustering algorith
BASE_DAO_DATAOPERATE
- 基于DAO的数据库操作，经过仔细的修改过，完全可以运行，里面注释很全，功能：把数据库中的记录显示到列表视图中，可以进行记录添加、删除、修改、查询等操作。-DAO-based database operations, the changes have been made carefully, can be run, which is the whole note, function: the database records show that the list view, you can rec
GA1E1
- 用Ｋ均值和遗传算法实现了半监督聚类算法，这是个一个已经发表的论文的源程序-Using K-means and genetic algorithm to achieve a semi-supervised clustering algorithm, this is a paper published source
chuankou2
- STM32F103的串口2中断读写，并且记录中断次数。-STM32F103 serial 2 interrupt to read and write and record the number of interrupts.
Source
- 本代码为了便于在VC++访问com组件的属性和接口函数而编写的类，使用时 只需要包含头文件"automation.h",类名为CAutomation。-Written this code in order to facilitate access to the properties of the com component and interface functions in VC class, use Only need to include the header file to "a
测距OK 10.19 save
- 基于407开发的VL53l0X程序，当然你也可以直接把代码文件拿出来用在其它地方，这是别人已经打包好了的。这里提一下，采集到的数据没有做任何的处理，提高精度需要自己去调试和滤波，大概有一个10-20的固差(The VL53l0X program based on 407, of course, you can also take the code file and use it elsewhere, which is already packed. The data collected here