用市面上的摄像头，可以实现实时人脸识别功能。(The algorithm model of facenet face recognition is obtained through deep learning, and the backbone network of feature extraction is concept-resnetv1, which is developed from concept network and RESNET, with more channels and n

使用Simulink(或m语言)仿真卷积编码，并用Viterbi译码的方法进行解码，其中的编码、译码全部是自己编写代码(m语言方式)，不是调用Simulink(或m语言)的已有编码、译码函数。并在加性白高斯噪声信道中，画出比特信噪比与误码率的关系曲线。(Simulink (or M language) is used to simulate convolutional coding, and Viterbi decoding method is used to decode, in which

图小波神经网络(GWNN)，一种新的图卷积神经网络(CNN)，利用图小波变换来解决以往光谱图CNN方法依赖于图傅立叶变换的缺点。(graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN met

论文U-Net: Convolutional Networks for Biomedical Image Segmentation的实现代码，使用Unet卷积神经网络，实现了细胞的轮廓识别。使用Python代码，keras框架。