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Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists.
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch
This book explores the fundamental computer vision principles and state-of-the-art algorithms used to create cutting-edge visual effects for movies and television.
This collection presents a unique multidisciplinary perspective on the problem of visual object categorization. The result of a series of four... Læs mere
Transfer learning deals with how machine learning and artificial intelligence systems can quickly adapt to new tasks and environments. This in-depth tutorial for students, researchers,... Læs mere
This 1998 book collects the ideas and algorithms from the world's leading scientists, offering a glimpse of the radical changes that could occur as a result of advances in computer vision.
This 2004 book is an introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A... Læs mere
Spread in 133 articles divided in 20 sections, this title broadly discusses: Image Processing; Radar and Satellite Image Processing;... Læs mere
This text is intended to help readers understand and construct machine vision systems that perform useful tasks, based on the state of the art. It covers fundamentals drawn from image processing and computer graphics to the methods of applied machine vision techniques.
Computer vision is the science and technology of machines that see. This book shows how, as a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images.