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鼠标，及界面演示 模拟Window
鼠标，及界面演示 模拟Window-mouse, and presentation interface simulation Window
- 2022-02-05 01:28:40下载
- 积分：1
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关键帧提取 K-mean方法
基于K-mean，也即是取K值法提取方法的关键帧抽取方法
- 2022-11-09 10:25:03下载
- 积分：1
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VGA动画显示
主要是通过将几幅图存储在FPGA中的几个RAM中，通过对不同的RAM内容的调取，实现动画的效果。该代码参考了黑金的建模的那些事儿完成的
- 2023-03-03 03:10:02下载
- 积分：1
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这个是一个用C 编的画图程序，显示坐标，和图像，是C 入门的好程序...
这个是一个用C 编的画图程序，显示坐标，和图像，是C 入门的好程序-This is a Paint program compiled with the C, display coordinates, and images, is a good entry procedures for C
- 2022-06-30 03:09:12下载
- 积分：1
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基本的绘图程序 画圆直线各类曲线 填充颜色等 不错
基本的绘图程序 画圆直线各类曲线 填充颜色等 不错-Basic drawing program drawcircle linear curve fill color, etc. all kinds of good
- 2022-03-18 02:27:40下载
- 积分：1
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图象压缩的处理，非常好用的代码，值得研究
图象压缩的处理，非常好用的代码，值得研究-Deal with image compression, very useful code, to be studied
- 2023-09-06 20:40:03下载
- 积分：1
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A color treatment of the VC source code, learning a good helper image processing
一个颜色处理的VC源程序，学习图像处理的好帮手-A color treatment of the VC source code, learning a good helper image processing
- 2022-10-06 11:50:03下载
- 积分：1
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LBP特征，局部二进制模式，非常简单和有用的
LBP特征，局部二进制模式，使用很方便.计算完后用局部区域的直方图描述其特征-LBP feature, Local Binary Pattern, very simple and usefull
- 2023-01-15 11:00:03下载
- 积分：1
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Image pattern recognition
图象模式识别--VC++技术实现
① 选择【模板匹配分类器】菜单，可以应用模板匹配算法进行分类。
② 选择【Bayes分类器】菜单，可以应用Bayes算法进行分类。
③ 选择【线性函数分类法】菜单，可以应用线性函数算法进行分类。
④ 选择【非线性分类法】菜单，可以应用非线性算法进行分类。
⑤ 选择【神经网络分类器】菜单，可以应用神经网络算法进行分类。
-Image pattern recognition- VC++ technology to achieve
- 2022-01-30 19:52:21下载
- 积分：1
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Abstract
We present a component
Abstract
We present a component-based, trainable system for detecting
frontal and near-frontal views of faces in still gray
images. The system consists of a two-level hierarchy of Support
Vector Machine (SVM) classifiers. On the first level,
component classifiers independently detect components of
a face. On the second level, a single classifier checks if the
geometrical configuration of the detected components in the
image matches a geometrical model of a face. We propose
a method for automatically learning components by using
3-D head models. This approach has the advantage that
no manual interaction is required for choosing and extracting
components. Experiments show that the componentbased
system is significantly more robust against rotations
in depth than a comparable system trained on whole face
patterns.
- 2023-05-01 18:35:08下载
- 积分：1
