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This book features high-quality research papers presented at the 3rd International Conference on Sustainable Expert Systems (ICSES 2022), held in Nepal during September 9–10, 2022. The book focuses on the research information related to artificial intelligence, sustainability and expert systems applied in almost all the areas of industries, government sectors and educational institutions worldwide. The main thrust of the book is to publish the conference papers that deal with the design, implementation, development, testing and management of intelligent and sustainable expert systems and also to provide both theoretical and practical guidelines for the deployment of these systems.
Techniques for high dynamic range (HDR) imaging make it possible to capture and store an increased range of luminances and colors as compared to what can be achieved with a conventional camera. This high amount of image information can be used in a wide range of applications, such as HDR displays, image-based lighting, tone-mapping, computer vision, and post-processing operations. HDR imaging has been an important concept in research and development for many years. Within the last couple of years it has also reached the consumer market, e.g. with TV displays that are capable of reproducing an increased dynamic range and peak luminance. This thesis presents a set of technical contributions within the field of HDR imaging. First, the area of HDR video tone-mapping is thoroughly reviewed, evaluated and developed upon. A subjective comparison experiment of existing methods is performed, followed by the development of novel techniques that overcome many of the problems evidenced by the evaluation. Second, a largescale objective comparison is presented, which evaluates existing techniques that are involved in HDR video distribution. From the results, a first open-source HDR video codec solution, Luma HDRv, is built using the best performing techniques. Third, a machine learning method is proposed for the purpose of reconstructing an HDR image from one single-exposure low dynamic range (LDR) image. The method is trained on a large set of HDR images, using recent advances in deep learning, and the results increase the quality and performance significantly as compared to existing algorithms. The areas for which contributions are presented can be closely inter-linked in the HDR imaging pipeline. Here, the thesis work helps in promoting efficient and high-quality HDR video distribution and display, as well as robust HDR image reconstruction from a single conventional LDR image.
Although we now have sophisticated algorithms and techniques for determining the shapes and sizes and for matching the fit between shoes and feet, few, if any, of the books currently available cover these new technologies until now. Bringing together high-quality and state-of-the-art contributions from designers, biomechanists, ergonomists, engineers, podiatrists, and scientists from industry and academia, The Science of Footwear provides an in-depth understanding of the technology and techniques involved in the design and development of a popular and demanding consumer product. This book introduces the design, development, manufacturing, and marketing of footwear. The chapters contain data from past research and the state-of-the art methodologies. They not only cover every aspect of the product design, but also how the footwear industry caters to the wide-ranging needs of sophisticated and demanding customers. The footwear industry has rapidly changed over the last 10 years. Mass production has changed to personalization and mass customization, areas that are not well-understood. This book explores these different concepts in a coherent way, drawing on differing views that give a holistic view of the science behind footwear. Collating information from different disciplines, the book provides the tools to develop the next generation of footwear.
The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material on development of computers for gaining understanding about videos and digital images. Highlighting a range of topics, such as computational models, machine learning, and image processing, this multi-volume book is ideally designed for academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.
With the advent of consumer-market Virtual Reality (VR) technology, the next revolution in visual entertainment is already on the horizon: real VR will enable us to experience live-action movies, sports broadcasts, concert videos, etc. in true visual (and aural) immersion. This book provides a comprehensive overview of the algorithms and methods that make it possible to immerse into real-world recordings. It brings together the expertise of internationally renowned experts from academia and industry who present the state of the art in this fascinating, interdisciplinary new research field. Written by and for scientists, engineers, and practitioners, this book is the definitive reference for anyone interested in finding out about how to import the real world into head-mounted displays.
Necessity is the mother of invention; challenging times can provide new opportunities that must be detected and exploited at the right moments. The COVID-19 pandemic has demonstrated that it is not only an issue of healthcare but also a challenge for the global economy, business, and society. Organizations have rapidly deployed technology solutions that enable them to work and service remotely and continue most of their normal operations. The Handbook of Research on Technologies and Systems for E-Collaboration During Global Crises focuses on emerging technologies and systems, strategies, and solutions for e-collaboration. This book assesses the importance of technologies and systems for e-collaboration in dealing with emerging crises such as pandemics. Covering topics such as deep learning processes, machine vision, and profit-sharing models, it is an essential resource for computer scientists, public officials, engineers, students and professors of higher education, healthcare administration, programmers, researchers, and academicians.
Camera Models and Fundamental Concepts Used in Geometric Computer Vision surveys the image acquisition methods used in computer vision and especially, of the vast number of camera models that have been proposed and investigated over the years, and points out similarities between different models.
This book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most noteworthy methods and results discussed at the International Conference on Reliability and Statistics in Transportation and Communication (RelStat), which took place in Riga, Latvia on October 16 – 19, 2019. It spans a broad spectrum of topics, from mathematical models and design methodologies, to software engineering, data security and financial issues, as well as practical problems in technical systems, such as transportation and telecommunications, and in engineering education.
Part of a two-volume set, this book constitutes the refereed proceedings of the Third Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007, held in Girona, Spain in June 2007. It covers pattern recognition, human language technology, special architectures and industrial applications, motion analysis, image analysis, biomedical applications, shape and texture analysis, 3D, and image coding and processing.
This book constitutes the refereed proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008, held in Juan-les-Pins, France, in October 2008. The 33 revised full papers and 69 posters presented were carefully reviewed and selected from 179 submissions. The papers are organized in topical sections on image and video coding; systems and applications; video processing; filtering and restoration; segmentation and feature extraction; tracking, scene understanding and computer vision; medical imaging; and biometrics and surveillance.