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Focusing on the design of content-based image and video retrieval systems, this book explores fundamental concepts and various design choices critical to these technologies. It offers a thorough survey of both research and commercial systems, supported by around 200 bibliographic references, including survey papers and recent works. Additionally, it features a detailed case study on MUSE, an image retrieval system developed at Florida Atlantic University, providing practical insights into system development and implementation.

Focusing on content-based image retrieval (CBIR), this book delves into organizing and retrieving visual information from large repositories. It addresses the challenges of the semantic gap between visual content and its interpretation, emphasizing the integration of textual metadata with pixel content for effective retrieval. The text provides an implementation-oriented overview of CBIR concepts, techniques, and algorithms, supported by practical Java examples using Lucene and LIRE. Key topics include visual features, indexing methods, and an introduction to relevant concepts in information retrieval.

Focusing on mobile visual computing, this book serves as a comprehensive guide for iOS developers and researchers. It covers essential concepts related to image processing and computer vision, equipping readers with the knowledge to create advanced iOS applications. The content is designed to enhance understanding and application of these technologies in real-world scenarios.

Artificial Intelligence has revolutionised areas of medicine. This book focuses on the integral role of AI in radiology, shedding light on how this technology can enhance patient care and streamline professional workflows.