Fundamentals of Computer Vision

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Release : 2017-09-28
Genre : Computers
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Book Rating : 828/5 ( reviews)

Fundamentals of 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 Fundamentals of Computer Vision write by Wesley E. Snyder. This book was released on 2017-09-28. Fundamentals of Computer Vision available in PDF, EPUB and Kindle. Computer vision has widespread and growing application including robotics, autonomous vehicles, medical imaging and diagnosis, surveillance, video analysis, and even tracking for sports analysis. This book equips the reader with crucial mathematical and algorithmic tools to develop a thorough understanding of the underlying components of any complete computer vision system and to design such systems. These components include identifying local features such as corners or edges in the presence of noise, edge preserving smoothing, connected component labeling, stereopsis, thresholding, clustering, segmentation, and describing and matching both shapes and scenes. The extensive examples include photographs of faces, cartoons, animal footprints, and angiograms, and each chapter concludes with homework exercises and suggested projects. Intended for advanced undergraduate and beginning graduate students, the text will also be of use to practitioners and researchers in a range of applications.

Computer Vision and Image Processing

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Release : 2019-11-05
Genre : Computers
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Book Rating : 383/5 ( reviews)

Computer Vision and Image Processing - 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 and Image Processing write by Manas Kamal Bhuyan. This book was released on 2019-11-05. Computer Vision and Image Processing available in PDF, EPUB and Kindle. The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts like object classification, object tracking, image-based rendering, and image registration. Intended to be a companion to a typical teaching course on computer vision, the book takes a problem-solving approach.

Computer Vision

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Release : 2012-06-18
Genre : Computers
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Book Rating : 795/5 ( reviews)

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.

Fundamentals of Deep Learning and Computer Vision

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Release : 2020-02-24
Genre : Computers
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Book Rating : 859/5 ( reviews)

Fundamentals of Deep Learning and 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 Fundamentals of Deep Learning and Computer Vision write by Nikhil Singh. This book was released on 2020-02-24. Fundamentals of Deep Learning and Computer Vision available in PDF, EPUB and Kindle. Master Computer Vision concepts using Deep Learning with easy-to-follow steps DESCRIPTIONÊ This book starts with setting up a Python virtual environment with the deep learning framework TensorFlow and then introduces the fundamental concepts of TensorFlow. Before moving on to Computer Vision, you will learn about neural networks and related aspects such as loss functions, gradient descent optimization, activation functions and how backpropagation works for training multi-layer perceptrons. To understand how the Convolutional Neural Network (CNN) is used for computer vision problems, you need to learn about the basic convolution operation. You will learn how CNN is different from a multi-layer perceptron along with a thorough discussion on the different building blocks of the CNN architecture such as kernel size, stride, padding, and pooling and finally learn how to build a small CNN model.Ê Next, you will learn about different popular CNN architectures such as AlexNet, VGGNet, Inception, and ResNets along with different object detection algorithms such as RCNN, SSD, and YOLO. The book concludes with a chapter on sequential models where you will learn about RNN, GRU, and LSTMs and their architectures and understand their applications in machine translation, image/video captioning and video classification. KEY FEATURESÊ Setting up the Python and TensorFlow environment Learn core Tensorflow concepts with the latest TF version 2.0 Learn Deep Learning for computer vision applicationsÊ Understand different computer vision concepts and use-cases Understand different state-of-the-art CNN architecturesÊ Build deep neural networks with transfer Learning using features from pre-trained CNN models Apply computer vision concepts with easy-to-follow code in Jupyter Notebook WHAT WILL YOU LEARNÊ This book will help the readers to understand and apply the latest Deep Learning technologies to different interesting computer vision applications without any prior domain knowledge of image processing. Thus, helping the users to acquire new skills specific to Computer Vision and Deep Learning and build solutions to real-life problems such as Image Classification and Object Detection. This book will serve as a basic guide for all the beginners to master Deep Learning and Computer Vision with lucid and intuitive explanations using basic mathematical concepts. It also explores these concepts with popular the deep learning framework TensorFlow. WHO THIS BOOK IS FOR This book is for all the Data Science enthusiasts and practitioners who intend to learn and master Computer Vision concepts and their applications using Deep Learning. This book assumes a basic Python understanding with hands-on experience. A basic senior secondary level understanding of Mathematics will help the reader to make the best out of this book.Ê Table of Contents 1. Introduction to TensorFlow 2. Introduction to Neural NetworksÊ 3. Convolutional Neural NetworkÊÊ 4. CNN Architectures 5. Sequential Models

Foundations of Computer Vision

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Release : 2024-04-16
Genre : Computers
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Book Rating : 973/5 ( reviews)

Foundations of 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 Foundations of Computer Vision write by Antonio Torralba. This book was released on 2024-04-16. Foundations of Computer Vision available in PDF, EPUB and Kindle. An accessible, authoritative, and up-to-date computer vision textbook offering a comprehensive introduction to the foundations of the field that incorporates the latest deep learning advances. Machine learning has revolutionized computer vision, but the methods of today have deep roots in the history of the field. Providing a much-needed modern treatment, this accessible and up-to-date textbook comprehensively introduces the foundations of computer vision while incorporating the latest deep learning advances. Taking a holistic approach that goes beyond machine learning, it addresses fundamental issues in the task of vision and the relationship of machine vision to human perception. Foundations of Computer Vision covers topics not standard in other texts, including transformers, diffusion models, statistical image models, issues of fairness and ethics, and the research process. To emphasize intuitive learning, concepts are presented in short, lucid chapters alongside extensive illustrations, questions, and examples. Written by leaders in the field and honed by a decade of classroom experience, this engaging and highly teachable book offers an essential next-generation view of computer vision. Up-to-date treatment integrates classic computer vision and deep learning Accessible approach emphasizes fundamentals and assumes little background knowledge Student-friendly presentation features extensive examples and images Proven in the classroom Instructor resources include slides, solutions, and source code