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A Deeper Vision

Author: Robert Royal

Publisher: Ignatius Press

Published: 2015-10-30

Total Pages: 621

ISBN-13: 158617990X

In this wide-ranging and ambitious volume, Robert Royal, a prominent participant for many years in debates about religion and contemporary life, offers a comprehensive and balanced appraisal of the Catholic intellectual tradition in the twentieth century. The Catholic Church values both Faith and Reason, and Catholicism has given risen to extraordinary ideas and whole schools of remarkable thought, not just in the distant past but throughout the troubled decades of the twentieth century. Royal presents in a single volume a sweeping but readable account of how Catholic thinking developed in philosophy, theology, Scripture studies, culture, literature, and much more in the twentieth century. This involves great figures, recognized as such both inside and outside the Church, such as Jacques Maritain, Bernard Lonergan, Joseph Pieper, Edith Stein, Alasdair MacIntyre, Charles Taylor, Romano Guardini, Karl Rahner, Henri du Lubac, Karol Wojtyla, Joseph Ratzinger, Hans Urs von Balthasar,Charles Peguy, Paul Claudel, George Bernanos, Francois Mauriac, G. K. Chesterton, Gerard Manley Hopkins, Christopher Dawson, Graham Greene, Sigrid Undset, J. R. R. Tolkien, Czeslaw Milosz, and many more. Royal argues that without rigorous thought, Catholicism – however welcoming and nourishing it might be – would become something like a doctor with a good bedside manner, but who knows little medicine. It has always been the aspiration of the Catholic tradition to unite emotion and intellect, action and contemplation. But unless we know what the tradition has already produced – especially in the work of the great figures of the recent past – we will not be able to answer the challenges that the modern world poses, or even properly recognize the true questions we face. This is a reflective, non-polemical work that brings together various strands of Catholic thought in the twentieth century. A comprehensive guide to the recent past - and the future.

Josef Sudek

Author: Josef Sudek

Publisher: Hirmer Verlag GmbH

Published: 2012

Total Pages: 0

ISBN-13: 9783777452913

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Josef Sudek, the 'Poet of Prague', had a legendary career spanning almost six decades. His craftsmanship and technical virtuosity were unparalleled among his contemporaries. Faced with the legacy of cubism, surrealism and the Czech avantgarde, Sudek sought his own approach, characterized by a striking mastery of light.

Spirituality in Photography

Author: Philip Richter

Publisher: Augsburg Books

Published: 2020-04-28

Total Pages: 122

ISBN-13: 1506467466

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Millions of photos are taken every day across the world. Some are just snapshots. Others are more carefully crafted and have the capacity to deepen our vision and sharpen our sense of what life is truly about. Spirituality in Photography explores how photography can offer unique perspectives on the self, the world, and what we live by. Readers are invited to take photos more slowly, reframe their gaze, allow themselves to be fully present, and let their photos tell a story--this includes a section on how photography can offer new perspectives on the Bible. The book also explores how photography can help readers meditate on mystery and tune into their own 'rule of life.' Spirituality in Photography offers a range of ideas for readers to try out with their camera or smartphone and invites them on a journey of discovery, as they allow their photography and their spirituality to inspire each other.

Deep Learning for Vision Systems

Author: Mohamed Elgendy

Publisher: Manning Publications

Published: 2020-11-10

Total Pages: 478

ISBN-13: 1617296198

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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

Sacred Fire

Author: Ronald Rolheiser

Publisher: Image

Published: 2017-03-14

Total Pages: 370

ISBN-13: 080413944X

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When one reaches the highest degree of human maturity, one has only one question left: How can I be helpful?—TERESA OF ÁVILA Beloved author Ronald Rolheiser continues his search for an accessible and penetrating Christian spirituality in this highly anticipated follow-up to the contemporary classic, The Holy Longing. With his trademark acuity, wit, and thoughtfulness, Rolheiser shows how identifying and embracing discipleship will lead to new heights of spiritual awareness and maturity. In this new book, Rolheiser takes us on a journey through the dark night of the senses and of the spirit. Here, we experience the full gamut of human life, pleasure and fervor, disillusionment and boredom. But, as Rolheiser explains, when we embrace the struggle and yearning to know God we can experience too a profound re-understanding to our daily lives. “What lies beyond the essentials, the basics?” Rolheiser writes. “Where do we go once some of the basic questions in our lives have been answered, or at least brought to enough peace that our focus can shift away from ourselves to others? Where do we go once the basic questions in our lives are no longer the restless questions of youthful insecurity and loneliness? Who am I? Who loves me? How will my life turn out? Where do we go once the basic question in life becomes: How can I give my life away more purely, and more meaningfully? How do I live beyond my own heartaches, headaches, and obsessions so as to help make other peoples’ lives more meaningful? The intent of this book is to try to address exactly those questions: How can we live less self- centered, more mature lives? What constitutes deep maturity and how do we reach that place? And, not unimportantly, what constitutes a more adult, Christian discipleship? What constitutes a truly mature following of Jesus?” As the poet Rainer Maria Rilke suggests, “Live the questions now.” In Sacred Fire, Rolheiser’s deeply affecting prose urges us on in pursuit of the most holy of all passions—a deep and lasting intimacy with God.

Deep Learning in Computer Vision

Author: Mahmoud Hassaballah

Publisher: CRC Press

Published: 2020-03-23

Total Pages: 261

ISBN-13: 1351003801

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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.

Toni Morrison's Spiritual Vision

Author: Nadra Nittle

Publisher: Augsburg Fortress Publishers

Published: 2021-10-05

Total Pages: 201

ISBN-13: 150647151X

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Toni Morrison's Spiritual Vision unpacks an oft-ignored but essential element of her work--her religion--and in so doing gives readers a deeper, richer understanding of her life and her writing. Nadra Nittle's wide-ranging, deep exploration of Morrison's oeuvre reveals the role of religion and spirituality in her life and literature.

Deep Learning

Author: Andrew Glassner

Publisher: No Starch Press

Published: 2021-06-22

Total Pages: 1239

ISBN-13: 1718500734

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A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare. Deep learning is the source of many of these breakthroughs, and its remarkable ability to find patterns hiding in data has made it the fastest growing field in artificial intelligence (AI). Digital assistants on our phones use deep learning to understand and respond intelligently to voice commands; automotive systems use it to safely navigate road hazards; online platforms use it to deliver personalized suggestions for movies and books - the possibilities are endless. Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals. If you want to know how these tools work, and use them yourself, the answers are all within these pages. And, if you're ready to write your own programs, there are also plenty of supplemental Python notebooks in the accompanying Github repository to get you going. The book's conversational style, extensive color illustrations, illuminating analogies, and real-world examples expertly explain the key concepts in deep learning, including: • How text generators create novel stories and articles • How deep learning systems learn to play and win at human games • How image classification systems identify objects or people in a photo • How to think about probabilities in a way that's useful to everyday life • How to use the machine learning techniques that form the core of modern AI Intellectual adventurers of all kinds can use the powerful ideas covered in Deep Learning: A Visual Approach to build intelligent systems that help us better understand the world and everyone who lives in it. It's the future of AI, and this book allows you to fully envision it. Full Color Illustrations

Deep Learning

Author: Ian Goodfellow

Publisher: MIT Press

Published: 2016-11-10

Total Pages: 801

ISBN-13: 0262337371

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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.

Fundamentals of Deep Learning and Computer Vision

Author: Nikhil Singh

Publisher: BPB Publications

Published: 2020-02-24

Total Pages: 222

ISBN-13: 9388511859

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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