- DemoVista VB模拟Vista窗体源码 === === === === === ===== 一个不错的vb模拟vista窗体源码
- auto_baud_RATE we ll start timer #1 in 16 bit mode at the transition between the start bit and the LSB and stop it between the MBS and stop bit. That will give approx the number of cpu cycles for 8 bits. Divide by 8 for one bit and by 16 since the built
- uvccapture-0.5.tar 针对USB摄像头采集
- 99252852 ICA MatLab Code Appendix D代码
- 轮廓提取 书法文字
- sobol Sobol全局敏感性分析Matlab代码
资源列表
paper_code_on_complex_network
- 六篇关于Complex Network的经典外文文献，有综述形文献，以及讲到如何建立网络模型的文献，对迅速建立起对Complex Network的理解有很大帮助。源程序是建立一个scale free network，注释详细，画出了P（K）图，可以观察r值。-Six foreign languages ??on Complex Network of classic literature, there is literature review form, and talked about how
CNN
- 用 卷积神经网络进行手写字符 识别,内含mnist训练集-Handwritten character recognition, containing mnist convolution neural network training set
ACO---Code-
- 蚁群算法和遗传算法的源码，性能比较，有搜索过程的界面显示，MFC框架-Ant colony optimization and Genetic Algorithm for TSP，developed in MFC
Deep Learning with Python(Fran?ois Chollet)
- 深度学习入门教程；使用python一步步教你走向大神之路(use python language to learn deeplearning)
Deep Learning with Python Keras
- 学深度学习的很棒的书 python keras 值得细读一波(Deep Learning with Python Keras)
nuerlnetwork.pdf
- 神经网络的一本经典著作,由著名的哈姆编写，现已绝版了-good book for nurel net work
sparse_coding_exercise
- 吴恩达UFLDL教程中关于稀疏编码的练习，很好很强大！-Andrew Ng UFLDL tutorial on sparse coding practice, very very powerful!
20081022
- 基于人工神经网络的图像识别方法研究。基于神经网络的人脸检测研究。基于特征融合与神经网络的手写体数字识别技基于遗传神经网络的手写体数字识别研究术研究。基于遗传优化的神经网络的银行票据手写数字识别。一种改进的人工神经网络模型-Based on artificial neural network image recognition method. Neural Network Based Face Detection Research. Based on Feature Fusion and Neur
Downloads
- neural networks tutorial
libdbn
- 基于马尔可夫毯的贝叶斯网络的结构学习算法-Based on Structure Learning Algorithm Markov Blanket Bayesian Networks
hasinoff-thesis-2008
- 这是一片关于如何获取图像中depth信息的文章。很有用。有参考价值-Variable-Aperture Photography. It is about how to get depth information in a photo.
NN
- 实现的一个用于手写数字识别的框架，可以设置神经网络结构，用的数据是mnist的(Implementation of a handwritten numeral recognition framework, you can set the neural network structure, the training data is MNIST)