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Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will ...

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Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, r...

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This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected f...

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Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning ...

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Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos Key Features Implement image classification and object detection using machine learning and deep learning Perform ...

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The field of pattern recognition has undergone substantial development over the last ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for...

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Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in O...

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Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features Discover best practices for engineering and maintaining OpenCV projects E...

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Explore OpenCV 4 to create visually appealing cross-platform computer vision applications Key Features Understand basic OpenCV 4 concepts and algorithms Grasp advanced OpenCV techniques such as 3D reconstruction, machine learning, and artificial n...

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Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key Features Learn about the new features that help unlock the full potential of OpenCV 4 Build face d...

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Highlights key research currently being undertaken within the field of telepresence, providing the most detailed account of the field to date, advancing our understanding of a fundamental property of all media - the illusion of presence; the sense...

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A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric pr...

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Hilbert space frames have long served as a valuable tool for signal and image processing due to their resilience to additive noise, quantization, and erasures, as well as their ability to capture valuable signal characteristics. More recently, fin...

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This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that ...

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This textbook offers a statistical view on the geometry of multiple view analysis, required for camera calibration and orientation and for geometric scene reconstruction based on geometric image features. The authors have backgrounds in geodesy an...

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This book presents a concise exposition of modern mathematical concepts, models and methods with applications in computer graphics, vision and machine learning. The compendium is organized in four parts - Algebra, Geometry, Topology, and Applicati...

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If you want a basic understanding of computer visions underlying theory and algorithms, this hands-on introduction is the ideal place to start. Youll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, an...

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Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features Understand the common architecture of different types of GANs Train, optimize, and deploy GAN applications using Tens...

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Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key Features Practical coverage of every image processing task with popular Python libraries Includes topics such as pseudo-colori...

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The original concept for the Vision in Vehicle series of international conferences was born from discussions within the Applied Vision Association which led eventually to the first conference being held in 1985. Ten years of progress later and thi...

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"e;Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?"e; If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build...

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In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, bio...

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This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form anal...

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Large volumes of video content can only be easily accessed by the use of rapid browsing and retrieval techniques. Constructing a video table of contents (ToC) and video highlights to enable end users to sift through all this data and find what the...

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Major strides have been made in face processing in the last ten years due to the fast growing need for security in various locations around the globe. A human eye can discern the details of a specific face with relative ease. It is this level of d...

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Based on the highly successful 3-volume reference Handbook of Computer Vision and Applications, this concise edition covers in a single volume the entire spectrum of computer vision ranging form the imaging process to high-end algorithms and appli...

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Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range...

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Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few. This new edition addresses and ...

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Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dr...

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New digital image processing and recognition methods, implementation techniques and advanced applications (television, remote sensing, biomedicine, traffic, inspection, robotics, etc.) are presented in this volume. Novel approaches (i.e. digital f...

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