Cosimo Distante

Paolo Spagnolo

Pier Luigi Mazzeo

This book provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing. Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including topics on systems design tools and techniques. Additionally, the book examines a varied range of applications. Features: contains valuable contributions from an international selection of leading experts in the field; presents a high-level introduction to the aims and motivations underpinning distributed sensing; describes decision-making algorithms in the presence of complex sensor networks; provides a detailed analysis of the design, implementation, and development of a distributed network of homogeneous or heterogeneous sensors; reviews the application of distributed sensing to human behavior understanding and autonomous intelligent vehicles; includes a helpful glossary and a list of acronyms.

Theory and Applications of Networks of Sensors

Human Behavior Understanding in Networked Sensing

Deep learning is a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. This book is divided into two sections. The first section covers deep learning architectures and the second section describes the state of the art of applications based on deep learning.

Deep Learning Applications

Srinivasan Ramakrishnan

Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.

Visual Object Tracking with Deep Neural Networks

Vincent Cottin

Wim A. Wuyts

Athol U. Wells

This Monograph provides expert clinical guidance on these difficult diseases, which will be helpful to both respiratory and nonrespiratory physicians alike. The initial chapters consider diagnostic issues, pulmonary function tests and techniques that are currently in development. The book then goes on to cover a variety of pulmonary manifestations of very different disease entities, such as connective tissue diseases, systemic vasculitis and much more.

Paolo Spagnolo

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