Practical Machine Learning for Computer Vision PDF Download

Author: Valliappa Lakshmanan
Publisher: "O'Reilly Media, Inc."
ISBN: 1098102339
Category : Computers
Languages : en
Pages : 481

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Book Description
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

Author: Borko Furht
Publisher: Springer Science & Business Media
ISBN: 0387747249
Category : Computers
Languages : en
Pages : 1031

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Book Description
This second edition provides easy access to important concepts, issues and technology trends in the field of multimedia technologies, systems, techniques, and applications. Over 1,100 heavily-illustrated pages — including 80 new entries — present concise overviews of all aspects of software, systems, web tools and hardware that enable video, audio and developing media to be shared and delivered electronically.

Author: Ioannis Pitas
Publisher: John Wiley & Sons
ISBN: 9780471377399
Category : Technology & Engineering
Languages : en
Pages : 436

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Book Description
A unique collection of algorithms and lab experiments for practitioners and researchers of digital image processing technology With the field of digital image processing rapidly expanding, there is a growing need for a book that would go beyond theory and techniques to address the underlying algorithms. Digital Image Processing Algorithms and Applications fills the gap in the field, providing scientists and engineers with a complete library of algorithms for digital image processing, coding, and analysis. Digital image transform algorithms, edge detection algorithms, and image segmentation algorithms are carefully gleaned from the literature for compatibility and a track record of acceptance in the scientific community. The author guides readers through all facets of the technology, supplementing the discussion with detailed lab exercises in EIKONA, his own digital image processing software, as well as useful PDF transparencies. He covers in depth filtering and enhancement, transforms, compression, edge detection, region segmentation, and shape analysis, explaining at every step the relevant theory, algorithm structure, and its use for problem solving in various applications. The availability of the lab exercises and the source code (all algorithms are presented in C-code) over the Internet makes the book an invaluable self-study guide. It also lets interested readers develop digital image processing applications on ordinary desktop computers as well as on Unix machines.

Author: Chetan Arora
Publisher: Springer Nature
ISBN: 9811513872
Category : Computers
Languages : en
Pages : 138

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Book Description
This book constitutes the refereed proceedings of the third Workshop on Computer Vision Applications, WCVA 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India, in December 2018. The 10 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers focus on computer vision; industrial applications; medical applications; and social applications.

Author: Sandipan Dey
Publisher: Packt Publishing Ltd
ISBN: 178934185X
Category : Computers
Languages : en
Pages : 483

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Book Description
Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.

Author: John W. Woods
Publisher: Academic Press
ISBN: 0123814219
Category : Computers
Languages : en
Pages : 617

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Book Description
Multidimensional Signal, Image, and Video Processing and Coding gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. Multidimensional Signal, Image, and Video Processing and Coding also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: - New appendices on random processes, information theory - New coverage of image analysis – edge detection, linking, clustering, and segmentation - Expanded coverage on image sensing and perception, including color spaces - Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC - Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding - More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming - New coverage of super-resolution methods for image and video - Only R&D level tutorial that gives an integrated treatment of image and video processing - topics that are interconnected - New chapters on introductory random processes, information theory, and image enhancement and analysis - Coverage and discussion of the latest standards in video coding: H.264/AVC and the new scalable video standard (SVC)

Author: Cyrille Rossant
Publisher: Packt Publishing Ltd
ISBN: 178328482X
Category : Computers
Languages : en
Pages : 899

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Book Description
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.

Author: Gene Cheung
Publisher: John Wiley & Sons
ISBN: 1789450284
Category : Computers
Languages : en
Pages : 322

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Book Description
Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.

Author: Wilhelm Burger
Publisher: Springer Science & Business Media
ISBN: 9781846283796
Category : Computers
Languages : en
Pages : 596

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Book Description
Written as an introduction for undergraduate students, this textbook covers the most important methods in digital image processing. Formal and mathematical aspects are discussed at a fundamental level and various practical examples and exercises supplement the text. The book uses the image processing environment ImageJ, freely distributed by the National Institute of Health. A comprehensive website supports the book, and contains full source code for all examples in the book, a question and answer forum, slides for instructors, etc. Digital Image Processing in Java is the definitive textbook for computer science students studying image processing and digital processing.

Author: Meiqing Wang
Publisher: CRC Press
ISBN: 1584888989
Category : Computers
Languages : en
Pages : 264

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Book Description
Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, con