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Great Singers

Glory of the Confessors

Gregory was bishop of Tours from 573. To most modern readers he is best known for his 'History of the Franks, ' a narrative of Gaul in the sixth century. But during his episcopacy Gregory of Tours also composed eight books of stories about saints, their cults, and their miracles. This volume is the first translation into English of one of those books, the 'Glory of the Confessors, ' which contains a series of anecdotes about the lives and cults of Christians who witnessed to their faith through their exemplary lives. These anecdotes provide important historical evidence, first, for the ways bishops and their congregations manipulated traditions about the development of the early church, and second, for the contemporary functions and meanings of the cults of saints during the sixth century. The spontaneity and literary modesty of many of the anecdotes make them especially valuable for modern historians intent upon understanding the early Frankish church.

A Guide to Convolutional Neural Networks for Computer Vision

Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs.The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.