男声女声识别程序

montecarlo算法，练习使用练习使用练习使用练习使用(montecarlo method montecarlo method)

CN对图像进行像素级的分类，从而解决了语义级别的图像分割（semantic segmentation）问题。与经典的CNN在卷积层之后使用全连接层得到固定长度的特征向量进行分类（全联接层＋softmax输出）不同，FCN可以接受任意尺寸的输入图像，采用反卷积层对最后一个卷积层的feature map进行上采样, 使它恢复到输入图像相同的尺寸，从而可以对每个像素都产生了一个预测, 同时保留了原始输入图像中的空间信息, 最后在上采样的特征图上进行逐像素分类。(CN classifies images at the pixel level, thus resolving the problem of semantic segmentation at the semantic level. Unlike classical CNN, which uses full-connection layer to get fixed-length feature vectors after convolution layer for classification (full-connection layer + soft Max output), FCN can accept any size of input image, and uses deconvolution layer to sample feature map of the last convolution layer to restore it to the same size of input image, so that each pixel can be generated. At the same time, the spatial information of the original input image is retained. Finally, the pixel-by-pixel classification is carried out on the feature map sampled above.)

在第一个图像中的每个描述符，选择它的匹配到第二个图像。(For efficiency in MATLAB, calculating dot multiplication between unit vectors is faster than Euclidean distance. Please note that: The ratio of attention to angle (the cosine of dot product of unit vector) is the approximate value of the ratio of Euclidean distance of small angle.)

说明：  abaqus周期性边界条件代码，可以参考学习(Periodic boundary conditions)

webQQ 的Python实现，亲测可以使用(webQQ Python implementation, pro-test can be used)

说明：  《Ｐｙｔｈｏｎ３反爬虫原理与绕过实战》随书源码，不错的资源哦("Python 3 anti crawler principle and bypass the actual combat" with the book source code, a good resource Oh)

gcn

【实例简介】数据转换与基本语法实例

说明：  对哔哩哔哩弹幕进行抽取并完成情感倾向的分析和估计(To extract bilibili barrage and complete the analysis and estimation of emotional tendency)

对哔哩哔哩弹幕进行抽取并完成情感倾向的分析和估计(To extract bilibili barrage and complete the analysis and estimation of emotional tendency)