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A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.

Multimedia systems. --- Internet of things. --- Machine learning. --- Multimedia Information Systems. --- Internet of Things. --- Machine Learning. --- Artificial intelligence. --- Computer simulation. --- Optical data processing.

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This book is a collection of the papers accepted by the ICIVIS 2022—The International Conference on Image, Vision and Intelligent Systems held on August 15–17, 2022, in Jinan, China. The topics focus but are not limited to image, vision and intelligent systems. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows and undergraduates as well as graduate students who need to build a knowledge base of the most current advances and state-of-practice in the topics covered by this conference proceedings.

Signal processing. --- Image processing. --- Machine learning. --- Signal, Speech and Image Processing . --- Image Processing. --- Machine Learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Computer vision --- Image processing

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Document layout analysis (DLA) is a crucial step towards the development of an effective document image processing system. In the early days of document image processing, DLA was not considered as a complete and complex research problem, rather just a pre-processing step having some minor challenges. The main reason for that is the type of layout being considered for processing was simple. Researchers started paying attention to this complex problem as they come across a large variety of documents. This book presents a clear view of the past, present, and future of DLA, and it also discusses two recent methods developed to address the said problem.

Image processing. --- Pattern recognition systems. --- Machine learning. --- Image Processing. --- Automated Pattern Recognition. --- Machine Learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Pattern classification systems --- Pattern recognition computers --- Pattern perception --- Computer vision --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing

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This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022. The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 883 delineated PET/CT images was made available for training. .

Image processing—Digital techniques. --- Computer vision. --- Image processing. --- Machine learning. --- Bioinformatics. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Image Processing. --- Machine Learning. --- Computational and Systems Biology. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Learning, Machine --- Artificial intelligence --- Machine theory --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems --- Data processing

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This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.

Medical informatics. --- Image processing—Digital techniques. --- Computer vision. --- Image processing. --- Machine learning. --- Artificial intelligence—Data processing. --- Health Informatics. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Image Processing. --- Machine Learning. --- Data Science. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Machine vision --- Vision, Computer --- Image processing --- Pattern recognition systems --- Clinical informatics --- Health informatics --- Medical information science --- Information science --- Medicine --- Data processing --- Internal Medicine --- Medical