Vision Machines


Book Description

Over the last decade, visibility and sexuality have become a major theme in Spanish and Cuban cinema, literature and art. Vision Machines explores this development in the light of contemporary history and recent theoretical accounts of sight by writers including Paul Virilio, Gianni Vattimo and Teresa de Lauretis. The very visible women of Almodóvar’s cinema are Paul Julian Smith’s first subject. He shows how, in his early Dark Habits, lesbianizes the look, putting women’s pleasure at the centre of the frame, and then examines Almodóvar’s recent film, Kika, where the conflict between cinema and video is played out in the bodies of women: good, bad and ugly. Moving the focus to Cuba, Smith discussed the reception in Europe and North America of Nestor Almendro’s remarkable documentary on gays in Cuba, Improper Conduct, and traces the trial of visibility to which effeminate men were exposed. He compares Amendor’s work with the autobiography of exile novelist Reinaldo Arenas, which revels in graphic sex, and also looks at the first Cuban film with a gay theme, Gutierrez Alea’s Strawberry and Chocolate. Smith returns to Spain to consider the response of artists and intellectuals to the public invisibility of AIDS in a country with one of the highest rates of HIV transmission in the Eurpean Union. Drawing on Anglo-American debates on the representation of AIDS, he concentrates on the one major intervention by Spanish scholars and artists, Love and Rage, and on the only figure in any medium to address AIDS in his aesthetic practice, the conceptual artist and video-maker Pepe Espaliu. He concludes with a fascinating account of Julio Medem’s pathbreaking film from 1993, The Red Squirrel, which has opened up a new approach to two formerly taboo subjects: Basque nationalism and female sexuality.




Peggy Ahwesh: Vision Machines


Book Description

"Since the early 1980s, American artist and filmmaker Peggy Ahwesh has forged a distinctive moving image practice in the ruins of originality and authority ... Peggy Ahwesh: Vision Machines explores how she has extended and contested the paradigm of experimental cinema over the last four decades."--Page 4 of cover.




The Vision Machine


Book Description

No Marketing Blurb




Handbook of Machine Vision


Book Description

With the demands of quality management and process control in an industrial environment machine vision is becoming an important issue. This handbook of machine vision is written by experts from leading companies in this field. It goes through all aspects of image acquisition and image processing. From the viewpoint of the industrial application the authors also elucidate in topics like illumination or camera calibration. Attention is paid to all hardware aspects, starting from lenses and camera systems to camera-computer interfaces. Besides the detailed hardware descriptions the necessary software is discussed with equal profoundness. This includes sections on digital image basics as well as image analysis and image processing. Finally the user is introduced to general aspects of industrial applications of machine vision, such as case studies and strategies for the conception of complete machine vision systems. With this handbook the reader will be enabled not only to understand up to date systems for machine vision but will also be qualified for the planning and evaluation of such technology.




Super-Intelligent Machines


Book Description

Super-Intelligent Machines combines neuroscience and computer science to analyze future intelligent machines. It describes how they will mimic the learning structures of human brains to serve billions of people via the network, and the superior level of consciousness this will give them. Whereas human learning is reinforced by self-interests, this book describes the selfless and compassionate values that must drive machine learning in order to protect human society. Technology will change life much more in the twenty-first century than it has in the twentieth, and Super-Intelligent Machines explains how that can be an advantage.




Machine Vision


Book Description

Aimed at manufacturing managers and engineers looking for an introduction to computer vision and its potential, this book discusses the areas in which machine vision is being used, explains different types of machine vision hardware and software and summarizes research at several universities.




Machine Vision


Book Description

Machine Vision: Theory, Algorithms, Practicalities covers the limitations, constraints, and tradeoffs of vision algorithms. This book is organized into four parts encompassing 21 chapters that tackle general topics, such as noise suppression, edge detection, principles of illumination, feature recognition, Bayes’ theory, and Hough transforms. Part 1 provides research ideas on imaging and image filtering operations, thresholding techniques, edge detection, and binary shape and boundary pattern analyses. Part 2 deals with the area of intermediate-level vision, the nature of the Hough transform, shape detection, and corner location. Part 3 demonstrates some of the practical applications of the basic work previously covered in the book. This part also discusses some of the principles underlying implementation, including on lighting and hardware systems. Part 4 highlights the limitations and constraints of vision algorithms and their corresponding solutions. This book will prove useful to students with undergraduate course on vision for electronic engineering or computer science.




Pattern Recognition by Humans and Machines


Book Description

Pattern Recognitions by Humans and Machines, Volume 2: Visual Perceptions covers aspects of research on visual perception. The book discusses visual form perception, figure-ground organization, and the spatial and temporal responses of the visual system; eye movements; and visual pattern perception. The text also describes a computer vision model based on psychophysical experiments; perspectives from brain theory and artificial intelligence; and the capacity to extract shape properties and spatial relations among objects and objects' parts. Knowledge-mediated perception is also considered. Psychologists and people involved in the study of visual perceptions will find the book useful.




Advances in Independent Component Analysis and Learning Machines


Book Description

In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning A diverse set of application fields, ranging from machine vision to science policy data Contributions from leading researchers in the field




Deep Learning for Vision Systems


Book Description

How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings