AE 2020中文版从入门到精通视频教程AE 2020入门到精通视频教程

JESD84-B51 Embedded Multi-Media Card(eMMC) Electrical Standard 5

陆其明《windows media编程导向》

NatDevice 是一款用于 iOS、Android、macOS 和 Windows 的跨平台媒体设备 API。NatDevice 提供强大的提取力来使用硬件摄像头和麦克风，通过一个简洁的NET API。

业界证实的GPU加速HAP视频编解码器的统一回放解决方案. 业界公认的GPU加速了统一的HAP视频编解码器重放解决方案. 特征： -(新)10k@50 fps回放 -(新)统一2017年支助 -(新)2个视频分辨率的非倍数 -(新)播放速度控制 -硬件加速HAP视频播放，无需安装任何外部编解码器。支持HAP和HAPQ。 -CPU/内存使用率低。在GPU上解压缩帧。 -播放4k@120 fps或8k@60 fps视频，同时播放多个视频。极快的帧精确搜索。 -带有Hap Alpha和Hap Q Alpha编解码器的透明视频。第一个插件，支持HAPQ阿尔法在统一。 -分块HAP支持更快的多线程解码。 -与大多数图形接口一起工作：DX9、DX 11、OpenGL、桌面平台上的金属。DX 12在路上！ -支持32位和64位构建！甚至在OSX上！ -通过统一本地音频插件和音频源输出音频。 -如果SSD不够快，可以预加载视频到内存 -适合程序员和艺术家：C#API以及IMGUI/uGUI包装器。 -典型使用场景的示例场景。 -免费演示版(以上链接) 本资产版本的要求： -团结5.x或团结2017.x -Windows 7/8/10 -OS X 10.9及以上

Windows Media Encoder及相关二次开发SDK, 完整的资料，可以结合我的博客看，支持AVi到wmv3 编解码等操作，

Media players for WALKMAN 1.42（港版提取）

Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing. Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure. It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies. The book emphasizes the big data aspects of social and digital media. It presents various approaches to storing vast amounts of data online and retrieving that data in real-time. It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems. It also covers emerging trends, such as big data analysis and social media evolution. Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs. It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more. This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution. It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks. Table of Contents Chapter 1 - Graphs in Social and Digital Media Chapter 2 - Mathematical Preliminaries: Graphs and Matrices Chapter 3 - Algebraic Graph Analysis Chapter 4 - Web Search Based on Ranking Chapter 5 - Label Propagation and Information Diffusion in Graphs Chapter 6 - Graph-Based Pattern Classification and Dimensionality Reduction Chapter 7 - Matrix and Tensor Factorization with Recommender System Applications Chapter 8 - Multimedia Social Search Based on Hypergraph Learning Chapter 9 - Graph Signal Processing in Social Media Chapter 10 - Big Data Analytics for Social Networks Chapter 11 - Semantic Model Adaptation for Evolving Big Social Data Chapter 12 - Big Graph Storage, Processing and Visualization

这是标清媒体播放器,源代码,这是一个完整的软件包.如有更多要求,联系wliness@126.com

WMFormatSDK WMFSDK 微软提供的用于windows音频、视频的软件开发包。适用于VC++等开发环境！