'Image Machine' examines the role of the photograph in Andy Warhol's art, its relationship to his portrait painting and his late paintings and prints, and his rigorous documentation of his social life.

This book is the first retrospective devoted to the greatest archive of news-gathering sources--the United Press International--which covers all aspects of American life, including sports, crime, celebrities, disasters, politics and more.

Beyond the Image Machine is an eloquent and stimulating argument for an alternative history of scientific and technological imaging systems. Drawing on a range of hitherto and marginalised examples from the world of visual representation and the work of key theorists and thinkers, such as Latour, de Certeau, McLuhan and Barthes, David Tomas offers a disarticulated and deviant view of the relationship between archaic and new representations, imaging technologies and media induced experience. Rejecting the possibility of absolute forms of knowledge, Tomas shows how new media technologies have changed the nature of established disciplines. The book develops Tomas's own theory of transcultural space and makes several original contributions to current debates on the culture of advanced technology.

"My stomach feels like it's tied up in a knot. My knees lock up, and my face feels hot. You know what I mean? I'm Wilma Jean, The Worry Machine." Anxiety is a subjective sense of worry, apprehension, and/or fear. It is considered to be the number one health problem in America. Although quite common, anxiety disorders in children are often misdiagnosed and overlooked. Everyone feels fear, worry and apprehension from time to time, but when these feelings prevent a person from doing what he/she wants and/or needs to do, anxiety becomes a disability. This fun and humorous book addresses the problem of anxiety in a way that relates to children of all ages. It offers creative strategies for parents and teachers to use that can lessen the severity of anxiety. The goal of the book is to give children the tools needed to feel more in control of their anxiety. For those worries that are not in anyone's control (i.e. the weather) a worry hat is introduced. A fun read for Wilmas of all ages! Includes a note to parents and educators with tips on dealing with an anxious child.

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book Load, store, edit, and visualize data using OpenCV and Python Grasp the fundamental concepts of classification, regression, and clustering Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn Explore and make effective use of OpenCV's machine learning module Learn deep learning for computer vision with Python Master linear regression and regularization techniques Classify objects such as flower species, handwritten digits, and pedestrians Explore the effective use of support vector machines, boosted decision trees, and random forests Get acquainted with neural networks and Deep Learning to address real-world problems Discover hidden structures in your data using k-means clustering Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google's DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.

Machine vision comprises three integrated processes: acquisition, preprocessing, and image analysis. While many resources discuss application-specific image analysis, there has been no unified account of image acquisition hardware and preprocessing - until now. This is a comprehensive, exhaustive reference text detailing every aspect of acquisition and preprocessing, from the illumination of a scene to the optics of image forming, from CCD and CMOS image capture to the transformation of the captured image.

Machine vision systems offer great potential in a large number of areas of manufacturing industry and are used principally for Automated Visual Inspection and Robot Vision. This publication presents the state of the art in image processing. It discusses techniques which have been developed for designing machines for use in industrial inspection and robot control, putting the emphasis on software and algorithms. A comprehensive set of image processing subroutines, which together form the basic vocabulary for the versatile image processing language IIPL, is presented. This language has proved to be extremely effective, working as a design tool, in solving numerous practical inspection problems. The merging of this language with Prolog provides an even more powerful facility which retains the benefits of human and machine intelligence. The authors bring together the practical experience and the picture material from a leading industrial research laboratory and the mathematical foundations necessary to understand and apply concepts in image processing. Interactive Image Processing is a self-contained reference book that can also be used in graduate level courses in electrical engineering, computer science and physics.