Selective Search的Python实现

说明：  用马尔可夫蒙特卡罗抽样从抽取样本，并拟合总体分布：正态分布、beta分布、t分布(Markov Monte Carlo sampling was used to extract samples and fit the population distribution: normal distribution, beta distribution and t distribution.)

说明：  实现强化学习，完成人工智能，实现机器学习，完成深度学习(Realize reinforcement learning, artificial intelligence, machine learning and deep learning)

说明：  图形自动编码器的pytorch实现，参考论文vgae(Implementation of graph self encoder gae with Python)

基于深度学习实现射频信号的调制识别，分别基于多种网络实现(Modulation Recognition of Radio Frequency Signals Based on Deep Learning)

说明：  fonte deconpilar bas

说明：  周期性边界条件，边界条件，周期性，周期性边界条件；(periodic boundary condition)

说明：  深度增强学习优化无人机航迹, 让无人机实现通信和计算任务(UAV trajectory optimization using deep reinforcement learning)

说明：  进行科学计算、数据处理用到的python教程,作为数据处理入门教程即可。转自嵩天老师的资料。(The course of data processing in scientific calculation)

基于树莓派B+版本的车牌识别设计，辨识部分以树莓派3B+/3B为核心处理器，基于Linux平台，通过python3.5和OpenCV来对含有车牌信息的图片，进行高斯去噪、灰度化、边缘检测、二值化、闭操作、字符分割、字符识别匹配等一系列图像处理操作最终实现车牌识别这个系统。(Based on the design of license plate recognition of raspberry pie B+version, the recognition part takes raspberry pie 3B+/3B as the core processor, and based on Linux platform, uses Python 3.5 and OpenCV to process the image containing license plate information, and carries out a series of image processing operations such as Gaussian denoising, graying, edge detection, binarization, closed operation, character segmentation, character recognition matching, etc. Finally, the system of license plate recognition is realized)

NTP Amplification attack