Download or read book A Vision of the Deep written by Susan Sutton and published by CLC Publications. This book was released on 2009-02-26 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Susan Sutton takes us beyond a sense of obligation and responsibility in the Christian life to give us a “vision of the deep.” If you are dissatisfied with “surface living,” join Susan in this life-altering venture to lose yourself in the fathomless depths of Jesus Christ.
Download or read book Deep Learning for Vision Systems written by Mohamed Elgendy and published by Manning Publications. This book was released on 2020-11-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Hidden Dimensions written by Dan Dyckman and published by Harmony. This book was released on 1994 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use your deep vision to solve mazes, riddles, and other perplexing puzzles.
Download or read book Deep Learning in Computer Vision written by Mahmoud Hassaballah and published by CRC Press. This book was released on 2020-03-23 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.
Download or read book A Vision of Fire written by Gillian Anderson and published by Simon and Schuster. This book was released on 2014-10-07 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Vision of Fire is the explosive first novel from iconic X-Files star Gillian Anderson and New York Times bestselling author Jeff Rovin: “Fans of Douglas Preston and Lincoln Child will find a lot to like” (Publishers Weekly). Renowned child psychologist Caitlin O’Hara is a single mom trying to juggle her job, her son, and a lackluster dating life. Her world is suddenly upturned when Maanik, the daughter of India’s ambassador to the United Nations starts speaking in tongues and having violent visions. Maanik’s parents are sure that her fits have something to do with the recent assassination attempt on her father—a shooting that has escalated nuclear tensions between India and Pakistan to dangerous levels—but when children start having similar outbursts around the world, Caitlin begins to think that there’s a stranger force at work. In Haiti, a student claws at her throat, drowning on dry land. In Iran, a boy suddenly and inexplicably bursts into flame. On the Pakistan border, a young man feels a burning in his chest and, against his will, opens fire on Indian troops. With Asia on the cusp of nuclear war, Caitlin must race across the globe and uncover the supernatural links between these seemingly unrelated cases in order to save her patient—and perhaps the world. The first in a series, A Vision of Fire is a pulse-pounding thriller that will leave you gasping for more.
Download or read book Advanced Methods and Deep Learning in Computer Vision written by E. R. Davies and published by Academic Press. This book was released on 2021-11-09 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. - Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field - Illustrates principles with modern, real-world applications - Suitable for self-learning or as a text for graduate courses
Download or read book The Valley of Vision written by Arthur Bennett and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Beneath written by Dale Mayer and published by Valley Publishing Ltd.. This book was released on 2019-01-01 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: You might think you know what lurks below, … but do you really? A kayaking incident off Seattle’s shores sends Whimsy into a coma, where her nightmares are a revolving repeat of her drowning. She wakes to life on an isolated island, involving her strange savior, two dogs with unique identities, and voices, sounds, emotions that aren’t hers alone. To a mystery that makes no sense … Samson heard the cry to save the woman washed onto his shores, and the dogs were already on the job before he arrived. But he had no idea how much impact this woman would make in his life … and his brother’s. However, the mystery is so much bigger than him and her … Plus another element is involved. A research group has been illegally conducting tests on the tectonic plates, … with unexpected consequences … deep beneath.
Download or read book Elements of Deep Learning for Computer Vision written by Bharat Sikka and published by BPB Publications. This book was released on 2021-06-24 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conceptualizing deep learning in computer vision applications using PyTorch and Python libraries. KEY FEATURES ● Covers a variety of computer vision projects, including face recognition and object recognition such as Yolo, Faster R-CNN. ● Includes graphical representations and illustrations of neural networks and teaches how to program them. ● Includes deep learning techniques and architectures introduced by Microsoft, Google, and the University of Oxford. DESCRIPTION Elements of Deep Learning for Computer Vision gives a thorough understanding of deep learning and provides highly accurate computer vision solutions while using libraries like PyTorch. This book introduces you to Deep Learning and explains all the concepts required to understand the basic working, development, and tuning of a neural network using Pytorch. The book then addresses the field of computer vision using two libraries, including the Python wrapper/version of OpenCV and PIL. After establishing and understanding both the primary concepts, the book addresses them together by explaining Convolutional Neural Networks(CNNs). CNNs are further elaborated using top industry standards and research to explain how they provide complicated Object Detection in images and videos, while also explaining their evaluation. Towards the end, the book explains how to develop a fully functional object detection model, including its deployment over APIs. By the end of this book, you are well-equipped with the role of deep learning in the field of computer vision along with a guided process to design deep learning solutions. WHAT YOU WILL LEARN ● Get to know the mechanism of deep learning and how neural networks operate. ● Learn to develop a highly accurate neural network model. ● Access to rich Python libraries to address computer vision challenges. ● Build deep learning models using PyTorch and learn how to deploy using the API. ● Learn to develop Object Detection and Face Recognition models along with their deployment. WHO THIS BOOK IS FOR This book is for the readers who aspire to gain a strong fundamental understanding of how to infuse deep learning into computer vision and image processing applications. Readers are expected to have intermediate Python skills. No previous knowledge of PyTorch and Computer Vision is required. TABLE OF CONTENTS 1. An Introduction to Deep Learning 2. Supervised Learning 3. Gradient Descent 4. OpenCV with Python 5. Python Imaging Library and Pillow 6. Introduction to Convolutional Neural Networks 7. GoogLeNet, VGGNet, and ResNet 8. Understanding Object Detection 9. Popular Algorithms for Object Detection 10. Faster RCNN with PyTorch and YoloV4 with Darknet 11. Comparing Algorithms and API Deployment with Flask 12. Applications in Real World
Download or read book Deep Learning for Computer Vision written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-04-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Download or read book The Vision Keepers written by Doug Alderson and published by Quest Books. This book was released on 2007-01-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are all seekers. Some find their path on pilgrimage to the Mahabodhi Temple in India or the Haji Ali mausoleum as they embark on a journey to Mecca; others find God at the burial site of St. James in the Cathedral de Santiago de Compostela in northwestern Spain. Author and environmentalist Doug Alderson meets the Great Spirit through the ancient spiritual practice of walking. The Vision Keepers is the compelling true story of a seeker who, under the guidance of Bear Heart, a Muskogee Creek Indian and Medicine Man, finds unity with our nation’s native people and reconnects with the earth through profound and mysterious means. At a time when our global community is in great conflict, we can learn much from Native Americans. The Vision Keepers not only recounts the story of one man’s experience with native people and their spirituality, but it offers unique insight into the struggles of an entire culture, personal reconciliation, world peace, and preservation of the Earth and its ancient wisdom.
Download or read book The Handwriting on the Wall written by James B. Jordan and published by American Vision. This book was released on 2007 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher's description: Jordan unravels the imagery of God's prophecies revealed in Daniel, events that were dawning in Daniel's lifetime.
Download or read book Deep Learning for Computer Vision written by Rajalingappaa Shanmugamani and published by Packt Publishing Ltd. This book was released on 2018-01-23 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key Features Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Book Description Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. What you will learn Set up an environment for deep learning with Python, TensorFlow, and Keras Define and train a model for image and video classification Use features from a pre-trained Convolutional Neural Network model for image retrieval Understand and implement object detection using the real-world Pedestrian Detection scenario Learn about various problems in image captioning and how to overcome them by training images and text together Implement similarity matching and train a model for face recognition Understand the concept of generative models and use them for image generation Deploy your deep learning models and optimize them for high performance Who this book is for This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book.
Download or read book Deep Purpose written by Ranjay Gulati and published by HarperCollins. This book was released on 2022-02-08 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thinkers50 Top 10 Best New Management Books for 2022 A distinguished Harvard Business School professor offers a compelling reassessment and defense of purpose as a management ethos, documenting the vast performance gains and social benefits that become possible when firms manage to get purpose right. Few business topics have aroused more skepticism in recent years than the notion of corporate purpose, and for good reason. Too many companies deploy purpose, or a reason for being, as a promotional vehicle to make themselves feel virtuous and to look good to the outside world. Some have only foggy ideas about what purpose is and conflate it with strategy and other concepts like “mission,” “vision,” and “values.” Even well-intentioned leaders don’t understand purpose’s full potential and engage half-heartedly and superficially with it. Outsiders spot this and become cynical about companies and the broader capitalist endeavor. Having conducted extensive field research, Ranjay Gulati reveals the fatal mistakes leaders unwittingly make when attempting to implement a reason for being. Moreover, he shows how companies can embed purpose much more deeply than they currently do, delivering impressive performance benefits that reward customers, suppliers, employees, shareholders, and communities alike. To get purpose right, leaders must fundamentally change not only how they execute it but also how they conceive of and relate to it. They must practice what Gulati calls deep purpose, furthering each organization’s reason for being more intensely, thoughtfully, and comprehensively than ever before. In this authoritative, accessible, and inspiring guide, Gulati takes readers inside some of the world’s most purposeful companies to understand the secrets to their successes. He explores how leaders can pursue purpose more deeply by navigating the inevitable tradeoffs more deliberately and effectively to balance between short- and long-term value; building purpose more systematically into every key organizational function to mobilize stakeholders and enhance performance; updating organizations to foster more autonomy and collaboration, which in turn allow individual employees to work more purposefully; using powerful storytelling to communicate a reason for being, arousing emotions and building a community of inspired and committed stakeholders; and building cultures that don’t merely support purpose, but also allow employees to link the corporate purpose to their own personal reasons for being. As Gulati argues, a deeper engagement with purpose holds the key not merely to the well-being of individual companies but also to humanity’s future. With capitalism under siege and relatively low levels of trust in business, purpose can serve as a radically new operating system for the enterprise, enhancing performance while also delivering meaningful benefits to society. It’s the kind of inspired thinking that businesses—and the rest of us—urgently need.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Download or read book A Vision Quest written by John S. Dunne and published by . This book was released on 2006 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seeking a vision like that of the great circle of love an old Bedouin described to Lawrence of Arabia, 'The love is from God and of God and towards God', this inspirational work features a series of meditations by the author, enriched by his wide-ranging insights.
Download or read book Practical Computer Vision Applications Using Deep Learning with CNNs written by Ahmed Fawzy Gad and published by Apress. This book was released on 2018-12-05 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model. After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads. This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. What You Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using PythonFollow a deep learning project from conception to production using TensorFlowUse NumPy with Kivy to build cross-platform data science applications Who This Book Is ForData scientists, machine learning and deep learning engineers, software developers.
