Today, audiovisual archives and libraries have become very popular especially in the field of collecting, preserving and transmitting cultural heritage. However, the data from these archives or libraries – videos, images, sound tracks, etc. – constitute as such only potential cognitive resources for a given public (or "target community"). They have to undergo more or less significant qualitative transformations in order to become user- or community-relevant intellectual goods. These qualitative transformations are performed through a series of concrete operations such as: audiovisual text segmentation, content description and indexing, pragmatic profiling, translation, etc. These and other operations constitute what we call the semiotic turn in dealing with digital (audiovisual) texts, corpora of texts or even entire (audiovisual) archives and libraries. They demonstrate practically and theoretically the well-known "from data to meta-data" or "from (simple) information to (relevant) knowledge" problem – a problem that obviously directly influences the effective use, the social impact and relevancy and therefore also the future of digital knowledge archives. It constitutes, indeed, the heart of a diversity of important R&D programs and projects all over the world.

"Designed for a course on image processing (IP) aimed at both graduate students as well as undergraduates in their senior year, in any field of engineering, this book starts with an overview in Chapter 1 of how imaging sensors--from cameras to radars to MRIs and CAT--form images, and then proceeds to cover a wide array of image processing topics. The IP topics include: image interpolation, magnification, thumbnails, and sharpening, edge detection, noise filtering, de-blurring of blurred images, supervised and unsupervised learning, and image segmentation, among many others. As a prelude to the chapters focused on image processing (Chapters 3-12), the book offers in Chapter 2 a review of 1-D signals and systems, borrowed from our 2018 book Signals and Systems: Theory and Applications, by Ulaby and Yagle."--Preface.

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

The Advances in Inorganic Chemistry series present timely and informative summaries of the current progress in a variety of subject areas within inorganic chemistry, ranging from bio-inorganic to solid state studies. This acclaimed serial features reviews written by experts in the field and serves as an indispensable reference to advanced researchers. Each volume contains an index, and each chapter is fully referenced. - Features comprehensive reviews on the latest developments - Includes contributions from leading experts in the field - Serves as an indispensable reference to advanced researchers

A cutting edge collection of 59 essays solicited from Web-based instructors offering a variety of perspectives, notions, and experiences in the practice of virtual teaching. The compendium introduces the evolution and status of distance learning, critical issues in Web-based learning environments such as the similarities and differences between Web-based and traditional classrooms, specific discussions on designing learning activities and electronic textbooks, an evaluation of delivery systems for instruction, and case studies of Web-based courses from kindergarten and beyond to the instruction of literature, astronomy, and foreign languages. Includes illustrations. Annotation copyrighted by Book News, Inc., Portland, OR