根据定义好的格式进行绘图

图案抖动技术处理系统源代码:bmp.h,dither.c-Pattern jitter treatment system source code: bmp.h, dither.c

资源描述基于贝叶斯的表情识别 非常清晰好理解

一个淡入淡出的图形编程，源代码内有详细的解释-fades out of a graphical programming source code with detailed explanations

界面程序，做得不错-interface procedures done well

RGB mixer. ideal for picture works

数字识别之神经网络法 数字训练、识别，功能强大-Digital Identification of the number of neural network training, identification, powerful

mallat实现信号的分解与重构，可帮助深刻理解mallat的意义-Mallat realize signal decomposition and reconstruction can help a deep understanding of the significance of Mallat

bmp文件read-bmp file read

streamline calculation

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.