Computer Vision - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computer Vision write by Simon J. D. Prince. This book was released on 2012-06-18. Computer Vision available in PDF, EPUB and Kindle. A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Practical Machine Learning for Computer Vision
Practical Machine Learning for Computer Vision - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Practical Machine Learning for Computer Vision write by Valliappa Lakshmanan. This book was released on 2021-07-21. Practical Machine Learning for Computer Vision available in PDF, EPUB and Kindle. This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
Computer Vision
Computer Vision - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computer Vision write by E. R. Davies. This book was released on 2017-11-15. Computer Vision available in PDF, EPUB and Kindle. Computer Vision: Principles, Algorithms, Applications, Learning (previously entitled Computer and Machine Vision) clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fifth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject. See an interview with the author explaining his approach to teaching and learning computer vision - http://scitechconnect.elsevier.com/computer-vision/ Three new chapters on Machine Learning emphasise the way the subject has been developing; Two chapters cover Basic Classification Concepts and Probabilistic Models; and the The third covers the principles of Deep Learning Networks and shows their impact on computer vision, reflected in a new chapter Face Detection and Recognition. A new chapter on Object Segmentation and Shape Models reflects the methodology of machine learning and gives practical demonstrations of its application. In-depth discussions have been included on geometric transformations, the EM algorithm, boosting, semantic segmentation, face frontalisation, RNNs and other key topics. Examples and applications—including the location of biscuits, foreign bodies, faces, eyes, road lanes, surveillance, vehicles and pedestrians—give the ‘ins and outs’ of developing real-world vision systems, showing the realities of practical implementation. Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples. The ‘recent developments’ sections included in each chapter aim to bring students and practitioners up to date with this fast-moving subject. Tailored programming examples—code, methods, illustrations, tasks, hints and solutions (mainly involving MATLAB and C++)
Computer Vision for Visual Effects
Computer Vision for Visual Effects - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computer Vision for Visual Effects write by Richard J. Radke. This book was released on 2013. Computer Vision for Visual Effects available in PDF, EPUB and Kindle. This book explores the fundamental computer vision principles and state-of-the-art algorithms used to create cutting-edge visual effects for movies and television. It describes classical computer vision algorithms and recent developments, features more than 200 original images, and contains in-depth interviews with Hollywood visual effects artists that tie the mathematical concepts to real-world filmmaking.
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multiple View Geometry in Computer Vision write by Richard Hartley. This book was released on 2004-03-25. Multiple View Geometry in Computer Vision available in PDF, EPUB and Kindle. 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 principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.
