From the visionary rebellion of Easy Rider to the reinvention of home in The Straight Story, the road movie has emerged as a significant film genre since the late 1960s, able to cut across a wide variety of film styles and contexts. Yet, within the variety, a certain generic core remains constant: the journey as cultural critique, as exploration beyond society and within oneself. This book traces the generic evolution of the road movie with respect to its diverse presentations, emphasizing it as an "independent genre" that attempts to incorporate marginality and subversion on many levels. David Laderman begins by identifying the road movie's defining features and by establishing the literary, classical Hollywood, and 1950s highway culture antecedents that formatively influenced it. He then traces the historical and aesthetic evolution of the road movie decade by decade through detailed and lively discussions of key films. Laderman concludes with a look at the European road movie, from the late 1950s auteurs through Godard and Wenders, and at compelling feminist road movies of the 1980s and 1990s.

A warm-hearted portrait of a simple event that encapsulates the bond between a father and a son. This warm and thoughtful story about a father and son on an all-night drive to the mountains is just right for Father's Day.

A groundbreaking approach to selling in a world demanding change Leaders, sales managers and professionals have found themselves stuck at a crossroads between the past and the future of selling, and they need a roadmap to help them embrace the challenges they face at such a critical juncture. Selling Vision is a step-by-step guide to creating and selling change. By implementing new change management strategies into their unique X→XY→Y selling methodology, the authors: · Propose a new logic for thinking about and executing major sales transformations · Examine these transformations from the customer’s perspective and how their changing buying patterns suggest a particular way of focusing selling activities · Consider the perspective of salespeople and what they can do to sell change to their customers · Look at how sales leaders and managers can change the way their organizations sell products or services · Highlight the pivotal moments that determine the success of major change initiatives Based on their unique X→XY→Y selling methodology, Schachter and Cheatham provide a proven sales strategy to help any sales leader, manager, or professional. For sales leaders, their approach provides a path for transforming the sales organization. For sales managers, it describes how to inspire change in the behavior of salespeople. And for salespeople, it offers a new way of selling that will have a dramatic impact on their performance. For any business executive, Selling Vision provides a faster path to driving change. This book provides immediate actions you can take and experiments you can conduct to find the right direction for future sales efforts at any level of an organization. How you respond to changing sales dynamics will determine your company’s success, that of your customers, and, to a great extent, your own personal career goals and future.

A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.

Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.

Anywhere But Here and The Lost Father have established Mona Simpson as one of our most accomplished writers. In her new novel--the portrait of a legendary, quintessentially American entrepreneur trapped by the age he helped to define--she brilliantly extends her achievement. More powerfully than ever before, Simpson uncovers the nature of longing and belonging, of blood relations and the human heart.

Become a better performance driver with Speed Secrets With the promise of autonomous vehicles in our near future, and current cars equipped with all sorts of mind-boggling driver aides, many feel that the art (and science) of performance driving has been lost - or will be. But no! For every device designed to take the act of driving out of our hands, the desire to actively participate in the control of a car becomes even stronger for driving enthusiasts. One only needs to look at the number of performance cars available today to see that the desire to truly drive is still in strong demand. In Speed Secrets: The Lost Art of Performance Driving, Ross Bentley explains in plain language how you can become an even better performance-oriented driver, whether it's to enjoy a twisty mountain highway, to take that secret back-road route to work, or to participate in a track day on a racing circuit. From how best to use your car's controls, to cornering, to dealing with adverse driving conditions, this book will make you a better performance driver. Along the way, you'll learn what ABS, traction and stability control, self-braking systems, and semi-automatic transmissions do and how best to incorporate them into your driving. Speed Secrets: The Lost Art of Performance Driving will help you understand your car well and be an even better, faster driver. Most importantly, it will fuel your passion for driving!

Masculinity, fast-changing and regularly declared to be in the throes of crisis, is attracting more popular and scholarly debate in China than ever before. At the same time, Chinese literature since 1989 has been characterized as brimming with countercultural ‘attitude’. This book probes the link between literary rebellion and manhood in China, showing how, as male writers critique the outcomes of decades of market reform, they also ask the same question: how best to be a man in the new postsocialist order? In this first full-length discussion of masculinity in post-1989 Chinese literature, Pamela Hunt offers a detailed analysis of four contemporary authors in particular: Zhu Wen, Feng Tang, Xu Zechen, and Han Han. In a series of insightful readings, she explores how all four writers show the same preoccupation with the figure of the man on the edges of society. Drawing on longstanding Chinese and global models of maverick, as well as marginal masculinity, and responding to a desire to retain a measure of masculine authority, their characters all engage in forms of transgression that still rely heavily on heteronormative and patriarchal values. Rebel Men argues that masculinity, so often overlooked in literary analysis of contemporary China, continues to be renegotiated, debated, and agonized over, and is ultimately reconstructed as more powerful than before. ‘An exceptionally lucid, elegant study of masculinity in mainland Chinese fiction of the 1990s and 2000s. Both historically and theoretically informed, Rebel Men: Masculinity and Attitude in Postsocialist Chinese Literature offers a major new perspective on post-1989 Chinese counterculture.’ —Julia Lovell, Birkbeck, University of London