action script viewer 汉化破解版，此版本为action script viewer 的汉化破解版，直接安装即可。

使用CNN进行动作识别 在该项目中，对卷积神经网络（CNN）进行了训练，以使用Pytorch对图像和视频进行分类。 数据集 使用过的UCF101数据http://crcv.ucf.edu/data/UCF101.php但仅接受了10个班级（共101个班级）。 每个剪辑有3帧，每帧为64 * 64像素。 片段的标签位于q3_2_data.mat 。 trLb是训练剪辑的标签，而valLb是验证剪辑的标签。 首先对CNN进行训练以对每个图像进行分类。 然后，使用3D卷积训练CNN，将每个剪辑分类为视频而不是图像 Kaggle比赛 CNN对图像的动作识别-排名第10- http://www.kaggle.com/c/cse512springhw3 CNN对视频的动作识别-排名32- http://www.kaggle.com/c/cse512springhw3video

本书摘自Chris Richardson撰写的POJOs in Action (ISBN 1932394583)，由Manning Publications公司出版，版权所有：2006年。 博文链接：https://projector.iteye.com/blog/209555

Unity in Action. 2nd Ed, 一本关于unity开发的英文书籍，初中级

MyActions 自己用来签到的东东,不支持售后 更新时间:2020-8-31 18:35:00 目前已支持 以及 中京东签到的内容,优点是支持无限数量的京东cookie 使用教程 直接fork走 再在Settings-Secrets里面添加JD_COOKIE 多条cookie用&隔开，支持无数条cookie 上面三步搞定后就不用管了 刚fork完可能在Actions中看不到对应的workflow 目前已配置好自动执行时间，到了指定时间会执行，并且看到workflow Secrets全集合 JD_COOKIE 【必须】京东Cookie，必须有这个，否则全部不执行 多个账号间用&隔开，支持无数个账号签到 PUSH_KEY 【可选】服务 用于推送Cookie失效通知，同时用于推送京东农场兑换礼物通知等 BARK_PUSH 【可选】BARK这个手机APP的推送 在settings->secre

Summary Web Components are a standardized way to build reusable custom elements for web pages and applications using HTML, CSS, and JavaScript. A Web Component is well-encapsulated, keeping its internal structure separate from other page elements so they don't collide with the rest of your code. In Web Components in Action you'll learn to design, build, and deploy reusable Web Components from scratch. Foreword by Gray Norton. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The right UI can set your sites and web applications apart from the ordinary. Using the Web Components API, you can build Custom Elements and then add them to your pages with just a simple HTML tag. This standards-based design approach gives you complete control over the style and behavior of your components and makes them radically easier to build, share, and reuse between projects. About the Book Web Components in Action teaches you to build and use Web Components from the ground up. You'll start with simple components and component-based applications, using JavaScript, HTML, and CSS. Then, you'll customize them and apply best design practices to maximize reusability. Through hands-on projects, you'll learn to build production-ready Web Components for any project, including color pickers, advanced applications using 3D models, mixed reality, and machine learning. What's inside Creating reusable Custom Elements without a framework Using the Shadow DOM for ultimate component encapsulation Leveraging newer JS features to organize and reuse code Fallback strategies for using Web Components on older browsers About the Reader Written for web developers experienced with HTML, CSS, and JavaScript. About the Author Ben Farrell is a Senior Experience Developer at Adobe working on the Adobe Design Prototyping Team.

中文名: SQL Server DMVs 实战 原名: SQL Server DMVs in Action: Better Queries with Dynamic Management Views 作者: Ian W. Stirk 资源格式: PDF 版本: 英文文字版/更新源代码 出版社: Manning书号: 9781935182733发行时间: 2011年05月 地区: 美国 语言: 英文 简介: 内容介绍： SQL Server DMVs in Action shows you how to obtain, interpret, and act on the information captured by DMVs to keep your system in top shape. The over 100 code examples help you master DMVs and give you an instantly reusable SQL library. You'll also learn to use Dynamic Management Functions (DMFs), which provide further details that enable you to improve your system's performance and health. 目录: Part 1 Starting the journey Chapter 1 The Dynamic Management Views gold mine Chapter 2 Common patterns Part 2 DMV discovery Chapter 3 Index DMVs Chapter 4 Improving poor query performance Chapter 5 Further query improvements Chapter 6 Operating system DMVs Chapter 7 Common Language Runtime DMVs Chapter 8 Resolving transaction issues Chapter 9 Database-level DMVs Chapter 10 The self-healing database Chapter 11 Useful scripts

主要给大家介绍Android 广播大全 Intent Action 事件详解，涉及到android广播action 方面知识点，本文讲解的非常的全面，感兴趣的朋友一起看看吧

Node Js In Action(中文版)

iDT-FV-for-action-recogniton iDT(mproved dense trajectories ) and Fisher Vector algorithm implement with C++ IDT + FisherVector编码 IDT 特征提取 IDT 的官方代码在这里 依赖的工具包是OpenCV2.4 和 ffmpeg. 然后编译产生 DenseTrack 可执行文件 然后就可以用这个可执行文件去提取自己的数据库视频特征啦。 注意的是产生的数据还是挺占存储空间的，所以最好压缩下。 举例： 我用的是NTU_RGB数据库，RGB模态的video.此数据库下的文件格式为： NTU_RGBD/nturgb+d_rgb_S001/videoname.avi 使用Linux下的shell 脚本：myIDT.sh 文件 Folder_A是我存放视频数据的路径 Fo