资源列表
matlabOCR
- matlab 文字识别 经典代码 文字分割 文字识别-Matlab character recognition classic code
framemarkers-2-0-7
- 高通增强现实源代码This Vuforia (TM) sample code provided in source code form (the "Sample Code") is made available to view for reference purposes only. If you would like to use the Sample Code in your software application, you must first download the Vuforia
cloudrecognition-2-0-7
- 高通增强现实源代码This Vuforia (TM) sample code provided in source code form (the "Sample Code") is made available to view for reference purposes only. If you would like to use the Sample Code in your software application, you must first download the Vuforia
backgroundtextureaccess-2-0-7
- 高通增强现实源码This Vuforia (TM) sample code provided in source code form (the "Sample Code") is made available to view for reference purposes only. If you would like to use the Sample Code in your software application, you must first download the Vuforia S
hog
- 人性检测HOG毕业设计,可以实现简单的人行检测-The human detection HOG graduation design
11
- 用C++软件编程并经过调试完整的人脸检测系统源码，附带图像-With the C++ software programming and debugging a complete face detection system source code, with the image
idwt_haar
- 应用matlab主要是实现图像识别，有非常好的应用-Application matlab image recognition, there is a very good application
bp
- 利用Bp神经网络实现文字的识别，识别性能较好，先将图像进行分割，然后利用神经网络进行识别-BP neural network text recognition, the recognition performance is better, the first image segmentation and recognition using neural network
chepaishibie2
- 神经网络实现车牌识别,通过图像分割，然后利用人工神经网络实现车牌号码的识别-Neural network license plate recognition, image segmentation, and then using artificial neural network license plate number identification
numerical-identities
- 应用matlab进行模式识别，主要针对图片中的数字进行识别，识别效率高-Application matlab pattern recognition, digital picture identification
numerical-recognition
- 应用BP神经网络对图片进行数字识别，设计GUI界面，操作简单。-BP neural network for digital identification, GUI interface design, simple operation.
SVM-KMExample
- 林智仁教授最新开发的libSVM工具箱的源码及程序注释，很详细的程序注释，对于学习SVM的人有很大的帮助-Professor Lin Zhiren newly developed libSVM of toolbox source code and program notes, a very detailed program notes, a great help for people learning SVM