A NEW YORK TIMES CRITICS' TOP BOOK OF THE YEAR • BOOKLISTS' EDITOR'S CHOICE • ONE OF NPR'S BEST BOOK OF THE YEAR “At once a film book, a history book, and a civil rights book.… Without a doubt, not only the very best film book [but] also one of the best books of the year in any genre. An absolutely essential read.” —Shondaland This unprecedented history of Black cinema examines 100 years of Black movies—from Gone with the Wind to Blaxploitation films to Black Panther—using the struggles and triumphs of the artists, and the films themselves, as a prism to explore Black culture, civil rights, and racism in America. From the acclaimed author of The Butler and Showdown. Beginning in 1915 with D. W. Griffith's The Birth of a Nation—which glorified the Ku Klux Klan and became Hollywood's first blockbuster—Wil Haygood gives us an incisive, fascinating, little-known history, spanning more than a century, of Black artists in the film business, on-screen and behind the scenes. He makes clear the effects of changing social realities and events on the business of making movies and on what was represented on the screen: from Jim Crow and segregation to white flight and interracial relationships, from the assassination of Malcolm X, to the O. J. Simpson trial, to the Black Lives Matter movement. He considers the films themselves—including Imitation of Life, Gone with the Wind, Porgy and Bess, the Blaxploitation films of the seventies, Do The Right Thing, 12 Years a Slave, and Black Panther. And he brings to new light the careers and significance of a wide range of historic and contemporary figures: Hattie McDaniel, Sidney Poitier, Berry Gordy, Alex Haley, Spike Lee, Billy Dee Willliams, Richard Pryor, Halle Berry, Ava DuVernay, and Jordan Peele, among many others. An important, timely book, Colorization gives us both an unprecedented history of Black cinema and a groundbreaking perspective on racism in modern America.

Obtain techniques for adding color to black and white or monochrome photographic images using GIMP. In this book you'll also learn to create a hand-tinted effect to add an element of antiquity. Pro Photo Colorizing with GIMP also teaches techniques that enable you to selectively colorize images, mixing black and white with color. There are also tips to go the opposite way: converting color images into black and white (there's more to it than just removing color). Written with both beginning and experienced GIMP users in mind, Pro Photo Colorizing with GIMP shows you how to colorize black and white images to achieve a high degree of realism. What You'll Learn Gain a basic overview of the GIMP workspace, tools, color palettes, layers, and layer masks Learn how to make the proper tonal adjustments to black and white images before starting the colorizing process Complete simple colorizing exercises for beginners and progress to more advanced colorizing techniques Colorize skin, teeth, hair, and eyes Create a nostalgic hand-tinted look and selectively colorize (mixing color with black and white) to create interesting images Use textures and patterns to create artistic colorized images Properly convert color images into black and white Colorize black and white portraits, and re-colorize old faded color portraits Who This Book Is For GIMP users (but users of other photo editing software packages can benefit as well). It is especially useful for those who edit photographs, restore old photographs, or those who want to apply colorizing techniques for artistic effect.

In Colorizing Restorative Justice, noted practitioners in restorative justice / practices offer accounts of their own experiences and critical analyses, as the book explores issues of race and marginalization within the field. The book illuminates how racism and colonization show up in the movement and includes thought-provoking questions to help readers fully process the articles.

This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.

"This book provides a complete overview of the state of the art in color image fusion, the associated evaluation methods, and its range of applications. It presents a comprehensive overview of fusion metrics and a comparison of objective metrics and subjective evaluations. Part I addresses the historical background and basic concepts. Part II describes image fusion theory. Part III focuses on quantitative and qualitative evaluation. Part IV presents several fusion applications, including two primary multiscale fusion approaches - the image pyramid and wavelet transform - as they pertain to face matching, biomedical imaging, and night vision"--

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book Description Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is for This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.

A New York Times Editors' Choice • Best Book of the Year: Time, NPR, Bookpage, L.A. Times What does it mean to be American? In this starkly illuminating and impassioned book, Pulitzer Prize­­–finalist Laila Lalami recounts her unlikely journey from Moroccan immigrant to U.S. citizen, using it as a starting point for her exploration of American rights, liberties, and protections. "Sharp, bracingly clear essays."—Entertainment Weekly Tapping into history, politics, and literature, she elucidates how accidents of birth—such as national origin, race, and gender—that once determined the boundaries of Americanness still cast their shadows today. Lalami poignantly illustrates how white supremacy survives through adaptation and legislation, with the result that a caste system is maintained that keeps the modern equivalent of white male landowners at the top of the social hierarchy. Conditional citizens, she argues, are all the people with whom America embraces with one arm and pushes away with the other. Brilliantly argued and deeply personal, Conditional Citizens weaves together Lalami’s own experiences with explorations of the place of nonwhites in the broader American culture.