资源列表
source-code
- 34个神经网络编程实例的源代码，采用matlab编写。详细的代码，一定收获颇丰-34 neural network programming examples. Detailed code, some rewarding
LBPSVM
- 实现了基于LBP和支持向量机的分类算法。首先提取出LBP特征，再利用支持向量机进行分类-Realized based on LBP and support vector machine (SVM) classification algorithm.First extract LBP feature, using support vector machine (SVM) classification
cannySVM
- 实现了基于canny算子和支持向量机的分类算法。首先提取出canny边缘特征，再利用支持向量机进行分类。-Realized based on canny operator and support vector machine (SVM) classification algorithm.First of all, extract the canny edge character, using support vector machine (SVM) classification.
ma
- 这是一个移动代理的综述文章，通过这几篇文章可以很好地了解在移动代理这块近期发展的情况-This is a review article on mobile agent can be well informed of recent developments in the mobile agent this through these articles
regression
- 这是线性回归与分类的材料，通过该材料很好地了解回归的知识-This is the material of linear regression and classification, a good knowledge of the material by the return of
antAlgorithm
- 这是一个蚁群算法的材料，该材料尅很好地了解蚁群算法的基本知识-This is an ant colony algorithm material that a good understanding of the basics of gram ant colony algorithm
PCA
- 这是一个关于PCA介绍的内容，该内容详细介绍了PCA的基本原理-This is a descr iption of the content on the PCA, the detailed descr iption of the basic principles of the PCA
multi-BP
- 这是一个介绍多层神经网络的资料，该资料详细简述了多层神经网络的基本原理-This is an introduction multilayer neural network data, the data in detail the basic principle of multilayer neural networks
partical-filter-tracking
- 这是一个基于粒子滤波的目标跟踪算法的完整代码，自己找个视频就可以了。大家可以参考一下~-the code for tracking based on particle filter
a-code-for-tracking-partical-filter
- 这是一个基于粒子滤波的目标跟踪算法的完整代码，自己找个视频就可以了。大家可以参考一下~-the code for tracking based on particle filter
Lplace
- 装载图像 使用高斯平滑消除噪声， 将图像转换到灰度空间。 使用Laplacian算子作用于灰度图像，并保存输出图像。 输出结果。-Loading image Use Gaussian smoothing to eliminate noise, the image is converted to grayscale space. Laplacian operator acting on grayscale images, and save the output image.
C-andy
- 加载一幅图片 对图片进行 标准霍夫线变换 或是 统计概率霍夫线变换. 分别在两个窗口显示原图像和绘出检测到直线的图像.-Load a picture The picture standard Hough transform line or line statistical probability Hough transform. Original image and draw a straight line detected image are shown in the tw