keras segnet代码

本书由Keras之父、现任Google人工智能研究员的弗朗索瓦?肖莱（Franc?ois Chollet）执笔，详尽介绍了用Python和Keras进行深度学习的探索实践，包括计算机视觉、自然语言处理、产生式模型等应用。书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立图像识别模型、生成图像和文字等能力。(This book is written by Franc_ois Chollet, the father of Keras and a current researcher on artificial intelligence at Google. It introduces in detail the exploratory practice of using Python and Keras for in-depth learning, including computer vision, natural language processing, production models and other applications. The book contains more than 30 code examples, the steps to explain in detail. Because the book is based on the accessibility and popularity of artificial intelligence, readers need not have the background knowledge of machine learning to start reading. After learning this book, readers will have the ability to build their own in-depth learning environment, establish image recognition model, generate images and text.)

baidu人脸识别Api例子, Baidu Face Recognition Api Example(Baidu Face Recognition Api Example)

说明：  深度学习入门 基于python的理论与实现 包含PDF版本和源码(Introduction to deep learning theory and Implementation Based on Python Contains PDF version and source code)

本文将以图像抠图领域的经典算法——贝叶斯抠图（Bayesian Matting）为例来介绍有关图像抠图技术的一些内容。贝叶斯抠图源自文献【2】，是2001年发表在CVPR上的一篇经典论文。(the image matting using classic bayesian approach)

说明：  TDOA通过四站定位，确定三个辅站从而计算出主站坐标(This code discrabes the tdoa about math)

语义依存方法的详细操作和编程思想，简明易懂，可以跟着编程(The detailed operation and programming idea of the semantic dependency method are concise and easy to understand, and can be followed by programming)

基于python的svm分类学习。线性可分svm，非线性svm。 对花卉（花蕾）进行分类，并可视化(SVM classification learning based on Python)

说明：  利用改进k-means算法对客户进行分类，改进rfm模型(Using improved k-means algorithm to classify customers and improve RFM model)

基于Python的OPC UA客户端的开发 源码下载(source code based on OPCua ,by Python)

一个普通的小游戏，没有什么功能，就一个垃圾小游戏(An ordinary little game, no function, just a junk game)