Everything you need to know to stay safe and secure when traveling abroad.
Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques. Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
The Senior s Guide to Computer Tips and Tricks
Rebecca Sharp Colmer A été écrit sous une forme ou une autre pendant la plus grande partie de sa vie. Vous pouvez trouver autant d'inspiration de The Senior s Guide to Computer Tips and Tricks Aussi informatif et amusant. Cliquez sur le bouton TÉLÉCHARGER ou Lire en ligne pour obtenir gratuitement le livre de titre $ gratuitement.
Education and the Commercial Mindset
The movement to privatize K–12 education is stronger than ever. Samuel Abrams examines the rise of market forces in public education and reveals how a commercial mindset that sidesteps fundamental challenges has taken over. Nevertheless, public schools should adopt lessons from the business world, such as raising teacher salaries to attract talent.
An Introduction to Statistical Learning
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Human Intelligence Counterterrorism and National Leadership
The next president of the United States faces innumerable complex problems, from a possible prolonged recession to climate change. An immediate difficulty for the president will be the global conflict between the West and Islamic jihadists and state sponsors of terrorism. The creation of the Department of Homeland Security and the recommendations of the 9/11 Commission notwithstanding, the administration needs to be armed and ready to tackle much more in the areas of intelligence and counterterrorism. The president can and must assume a hands-on, informed leadership role if the United States wants to make progress in the war on terror. Gary Berntsen has written this book as a guide for an incoming president and White House staff so that they may master current human intelligence and counterterrorism operations. After reading its highly specific recommendations and policy prescriptions, the president and his or her staff will be able to draft a First Directive for the leadership of the intelligence and national security communities outlining how the administration wants those communities to proceed and to defend the nation's interests. Human Intelligence, Counterterrorism, and National Leadership will be of interest to legislators, policymakers, and anyone concerned about intelligence and terrorism policy. With a foreword by Seth G. Jones, a political scientist at the RAND Corporation and Adjunct Professor in the Security Studies Program at Georgetown University. He is the author of In the Graveyard of Empires: America's War in Afghanistan and The Rise of European Security Cooperation.
Windows 10 for Seniors
The ideal book for older adults that have already worked with an earlier version of Windows and want to get up and going with Windows 10, this guide covers all of the important basic functions, including browsing the internet safely, sending and receiving email, organizing files and folders, viewing photos and videos, and listening to music. The book allows users to learn step by step and at their own pace how to work with the new programs and features in Windows 10, as well as how to configure Windows 10 to make their computers more user-friendly. It offers additional exercises for practicing a variety of different tasks, and there are instructional videos available online on the book's support website.
But Don t All Religions Lead to God
We've all heard the rationale: "It doesn't matter what you believe as long as you're sincere." Or "All religions are pretty much the same." But are they the same? Does it matter which one you follow? In this insightful and compelling book, Michael Green invites readers into a relationship with Jesus Christ, the divine revelation and only pathway to the one true God. In a conversational style geared toward nonbelievers, Green compares Christianity, Buddhism, Islam, and other religions to help spiritual seekers navigate the multi-faith maze. "But Don't All Religions Lead to God?" is an ideal reference and evangelism tool for churches and individual Christians as well. It offers scriptural references, looks at how divergent religious traditions view salvation and eternity, and answers difficult questions such as "What about people who have never heard of Jesus?" and "How should Christians regard other religions?" In the midst of our pluralistic and tolerant culture, here is an important and convincing argument for faith in Jesus-the only great teacher whose death and resurrection provided grace, forgiveness, and an eternity in the presence of God.
Web Data Mining
Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web data. The field has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
World Development Indicators 2013
World Development Indicators is the premier annual compilation of data on development. This year's edition was redesigned to allow users the convenience of easily linking to the latest data online.