IOP Series in Next Generation Computing – serie

VLSI is a well-established field of research that ignited the modern computing revolution. Serving as a guide to future developments, this book provides a framework for design, modeling concepts, and application of Image Processing based systems using VLSI design techniques. This volume focuses on a range of topics including object detection, recognition, smart traffic management, surveillance systems, face detection, gesture-based automated systems, and smart cities based on automated cameras. The book will help the research community to get in-depth knowledge of various systems that can be designed with image processing techniques using hardware.

Key Features:

Describes concepts of state-of-the-art Image processing-based VLSI Design.Describes the Hardware implementation of image and video processing algorithms.Offers real-time hardware system design for smart citiesDevelops dedicated hardware design for medical image processing applicationsExplores VLSI design for cognitive science, augmented reality and virtual reality

Artificial intelligence is gaining traction in areas of social responsibility. From climate change to social polarization to epidemics, humankind has been seeking new solutions to these ever-present problems. Deep Learning (DL) techniques have increased in power in recent years, with algorithms already exhibiting tremendous possibilities in domains such as scientific research, agriculture, smart cities, finance, healthcare, conservation, the environment, industry and more. Innovative ideas using appropriate DL frameworks are now actively employed for the development and delivering a positive impact on smart cities and societies. This book highlights the importance of specific frameworks such as IoT-enabled frameworks or serverless cloud frameworks that are applying DL techniques for solving persistent societal problems. It addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modelling different types of data. In particular, the book explores and emphasises techniques involved in deep learning such as image classification, image enhancement, word analysis, human-machine emotional interfaces and the applications of these techniques for smart cities and societal problems. To extend a theoretical description the book is enhanced through case studies, including those implemented using tensorflow2 and relevant IoT-specific sensor/actuator frameworks. The broad coverage will be essential reading not just to advanced students and academic researchers but also to practitioners and engineers looking to deliver an improved society and global health.

Key Features

A unique focus on societal improving applications of DL technologies The book starts with a broader perspective before delving into the specific topics of the deep learning domain. Each chapter looks at future application paths as well as present usage. Showcases working code that reveals DL aspects in the context of smart cities or societies. Chapters include learning objectives and summaries.

This edited book focuses on well-known and new methodologies of optimization techniques in human-assisted computing that are used to resolve some of the very complicated and hard problems we face today