This book constitutes the proceedings of the Third International Conference on Smart Multimedia, ICSM 2022, which was held in Marseille, France, during August 25–27, 2022. The 30 full papers and 4 short paper presented in this volume were carefully reviewed and selected from 68 submissions. The contributions were organized in topical sections as follows: Machine Learning for Multimedia; Image Processing; Multimedia Applications; Multimedia for Medicine and Health-Care; Smart Homes; Multimedia Environments and Metaverse; Deep Learning on Video and Music; Haptic; Industrial.

Automation and Computational Intelligence for Road Maintenance and Management A comprehensive computational intelligence toolbox for solving problems in infrastructure management In Automation and Computational Intelligence for Road Maintenance and Management, a team of accomplished researchers delivers an incisive reference that covers the latest developments in computer technology infrastructure management. The book contains an overview of foundational and emerging technologies and methods in both automation and computational intelligence, as well as detailed presentations of specific methodologies. The distinguished authors emphasize the most recent advances in the maintenance and management of infrastructure robotics, automated inspection, remote sensing, and the applications of new and emerging computing technologies, including artificial intelligence, evolutionary computing, fuzzy logic, genetic algorithms, knowledge discovery and engineering, and more. Automation and Computational Intelligence for Road Maintenance and Management explores a universal synthesis of the cutting edge in parameters and indices to evaluate models. It also includes: Thorough introductions to management science and the latest methods of automation and the structure and framework of automation and computing intelligence Comprehensive explorations of advanced image processing techniques, recent advances in fuzzy, and diagnosis automation Practical discussions of segmentation and fragmentation and different types of features and feature extraction methods In-depth examinations of methods of classification along with various developed methodologies and models of quantification, evaluation, and indexing in automation Perfect for postgraduate students in road and transportation engineering, evaluation, and assessment, Automation and Computational Intelligence for Road Maintenance and Management will also earn a place in the libraries of researchers interested in or working with the evaluation and assessment of infrastructure.

The 27th EG-ICE International Workshop 2020 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. Der 27. Internationale EG-ICE Workshop 2020 bringt internationale Experten zusammen, die an der Schnittstelle zwischen fortgeschrittener Datenverarbeitung und modernen technischen Herausforderungen arbeiten. Viele ingenieurwissenschaftliche Aufgaben erfordern Open-World-Resolutionen, um die Zusammenarbeit mehrerer Akteure zu unterstützen, mit approximativen Modellen umzugehen, eine effektive Interaktion zwischen Ingenieur und Computer zu ermöglichen, in mehrdimensionalen Lösungsräumen zu suchen, Unsicherheiten zu berücksichtigen, einschließlich fachspezifischen Domänenwissens, Sensordateninterpretation durchzuführen und mit unvollständigem Wissen umzugehen. Während die Ergebnisse aus der Informatik anfänglich viel Unterstützung für die Lösung bieten, ist eine Anpassung unvermeidlich, und am wichtigsten ist, dass das Feedback aus der Bewältigung technischer Herausforderungen die computer-wissenschaftliche Grundlagenforschung vorantreibt. Kompetenz und Wissenstransfer gehen in beide Richtungen.

Infrared thermography (IRT) is a non-contact, non-invasive methodology which allows for detection of thermal energy that is radiated from objects in the infrared band of the electromagnetic spectrum, for conversion of such energy into a visible image (such as a surface temperature map). This feature represents a great potential to be exploited in a vast variety of fields from aerospace to civil engineering, to medicine, to agriculture, etc. However, IRT is still not adequately enclosed in industrial instrumentation and there are still potential users who might benefit from the use of such a technique and who are not aware of their existence. This e-book conveys information about basic IRT theory, infrared detectors, signal digitalization and applications of infrared thermography in many fields such as medicine, foodstuff conservation, fluid-dynamics, architecture, anthropology, condition monitoring, non destructive testing and evaluation of materials and structures. The volume promotes an exchange of information between the academic world and industry, and shares methodologies which were independently developed and applied in specific disciplines.

Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.

This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as for example, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computational vision, computer sciences, human motion, mathematics, medical imaging, medicine, pattern recognition and physics.

The past decade has seen tremendous interest in the production and refinement of unmanned aerial vehicles, both fixed-wing, such as airplanes and rotary-wing, such as helicopters and vertical takeoff and landing vehicles. This book provides a diversified survey of research and development on small and miniature unmanned aerial vehicles of both fixed and rotary wing designs. From historical background to proposed new applications, this is the most comprehensive reference yet.