机器学习数据增强代码-平移、旋转、加噪声

卡尔曼滤波的一个典型实例是从一组有限的，包含噪声的，对物体位置的观察序列（可能有偏差）预测出物体的位置的坐标及速度。在很多工程应用(如雷达、计算机视觉)中都可以找到它的身影。同时，卡尔曼滤波也是控制理论以及控制系统工程中的一个重要课题。(A typical example of the Kalman filter, from a limited set, containing the noise, the position of the object observed sequence (there may be deviation) to predict the coordinates of the location and speed of the object. Its presence can be found in many engineering applications (such as radar, computer vision). Meanwhile, the Kalman filter is control theory, and control is an important topic in systems engineering.)

说明：  可以批量嵌入cohesiveelements，0厚度单元，abaqus使用(Embeddable cohesiveelements in batches, 0 thickness unit for abaqus use)

有需要的可以查看，对毕业生有一点帮助

说明：  周志华 机器学习 机器学习是计算机科学与人工智能的重要分支领域. 本书作为该领域的入门教材，在内容上尽可能涵盖机器学习基础知识的各方面。 为了使尽可能多的读者通过本书对机器学习有所了解。 作者试图尽可能少地使用数学知识. 然而, 少量的概率、统计、代数、优化、逻辑知识似乎不可避免. 因此, 本书更适合大学三年级以上的理工科本科生和研究生, 以及具有类似背景的对机器学 习感兴趣的人士. 为方便读者, 本书附录给出了一些相关数学基础知识简介(machine learningMachine learning is an important branch of computer science and artificial intelligence. As an introductory textbook in this field, this book covers all aspects of basic knowledge of machine learning as far as possible. In order to make as many readers as possible understand machine learning through this book. The author tries to use mathematical knowledge as little as possible. However, a small amount of knowledge about probability, statistics, algebra, optimization and logic seems inevitable. Therefore, this book is more suitable for undergraduates and postgraduates of science and engineering over the third year of the University, as well as people with similar background who are interested in machine learning. For the convenience of readers, the appendix of this book gives some basic mathematical knowledge)

通过四则运算得24的计算方法显示；特别是整数只能通过小数运算，得到24的神奇解。

基于FPGA的图像sobel算法，利用quartus软件对程序调制后写入FPGA以进行图像的SOBEL处理。

矩阵计算，包括加减乘，反矩阵，python源码，可以直接使用(matrix calculation)

图书管理系统 使用说明 功能演示： 下载整个程序包，确保系统有python3环境，打开cmd，输入命令（替换成本机的工程目录地址）： python F:ook_management_sysook_management_sys.py runserver 浏览器输入 http://127.0.0.1:5000/ 进入系统 系统分两类用户：普通读者用户，管理员用户。 普通读者用户可以查看图书信息和查看借阅记录，在登录页顶端导航栏切换功能，不用输入用户名、密码。 管理员用户可使用一切功能，账号、密码登陆后，进行日常业务操作。 测试数据： 图书信息书名可填写“学习”“机器”，类别可填写“计算机”等；学生借阅卡可填写：16000001,16000002,16000003（该卡无借阅记录）；

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)

说明：  基于深度学习的脑肿瘤分割,模型使用的是DenseUnet,使用python语言(Brain tumor segmentation based on deep learning, the model uses DenseUnet, and python language)