Vania V. Estrela – författare

The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.

The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.

Feeding an expanding population in light of environmental preservation and keeping production lean is a considerable challenge. Sustainable and Precise Agriculture relying on Industry 4.0 (Agri4) points toward creating strategic collaborations, innovations, and alternative approaches to old concerns, and incorporating solutions from other expertise domains. It requires intensive efforts from governments, investors, investigators, and developers. These initiatives address many problems while connecting more agrarians and their communities. Agri4 entails key agribusiness developments, viz. precision agriculture, biotech, IoT, and Big Data, to augment efficiency in dealing with growing population and climate change. Agri4 is likely to yield improvements such as sustainable practices education, environmental residue reduction, seed improvement, and traditional agricultural knowledge usage, among others. It promotes sustainable food production, community development, and scientific literacy by fostering effective natural resource administration.This book explores the transformative impact of Agriculture 4.0, guiding readers through the integration of digital technologies and sustainable practices into modern farming. It discusses how innovations like AI and the IoT are revolutionizing agriculture, enhancing connectivity, precision, and ecological awareness. The intended readers of the book include agricultural professionals, researchers, tech innovators, policymakers, and students. It caters to those interested in the convergence of modern technology and farming, particularly in advancing sustainable practices and understanding the future of agriculture in the digital age.

Feeding an expanding population in light of environmental preservation and keeping production lean is a considerable challenge. Sustainable and Precise Agriculture relying on Industry 4.0 (Agri4) points toward creating strategic collaborations, innovations, and alternative approaches to old concerns, and incorporating solutions from other expertise domains. It requires intensive efforts from governments, investors, investigators, and developers. These initiatives address many problems while connecting more agrarians and their communities. Agri4 entails key agribusiness developments, viz. precision agriculture, biotech, IoT, and Big Data, to augment efficiency in dealing with growing population and climate change. Agri4 is likely to yield improvements such as sustainable practices education, environmental residue reduction, seed improvement, and traditional agricultural knowledge usage, among others. It promotes sustainable food production, community development, and scientific literacy by fostering effective natural resource administration.This book explores the transformative impact of Agriculture 4.0, guiding readers through the integration of digital technologies and sustainable practices into modern farming. It discusses how innovations like AI and the IoT are revolutionizing agriculture, enhancing connectivity, precision, and ecological awareness. The intended readers of the book include agricultural professionals, researchers, tech innovators, policymakers, and students. It caters to those interested in the convergence of modern technology and farming, particularly in advancing sustainable practices and understanding the future of agriculture in the digital age.

This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS).Volume 1 concentrates on UAS control and performance methodologies including Computer Vision and Data Storage, Integrated Optical Flow for Detection and Avoidance Systems, Navigation and Intelligence, Modeling and Simulation, Multisensor Data Fusion, Vision in Micro-Aerial Vehicles (MAVs), Computer Vision in UAV using ROS, Security Aspects of UAV and Robot Operating System, Vision in Indoor and Outdoor Drones, Sensors and Computer Vision, and Small UAV for Persistent Surveillance.Volume 2 focuses on UAS deployment and applications including UAV-CPSs as a Testbed for New Technologies and a Primer to Industry 5.0, Human-Machine Interface Design, Open Source Software (OSS) and Hardware (OSH), Image Transmission in MIMO-OSTBC System, Image Database, Communications Requirements, Video Streaming, and Communications Links, Multispectral vs Hyperspectral Imaging, Aerial Imaging and Reconstruction of Infrastructures, Deep Learning as an Alternative to Super Resolution Imaging, and Quality of Experience (QoE) and Quality of Service (QoS).

This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS).Volume 1 concentrates on UAS control and performance methodologies including Computer Vision and Data Storage, Integrated Optical Flow for Detection and Avoidance Systems, Navigation and Intelligence, Modeling and Simulation, Multisensor Data Fusion, Vision in Micro-Aerial Vehicles (MAVs), Computer Vision in UAV using ROS, Security Aspects of UAV and Robot Operating System, Vision in Indoor and Outdoor Drones, Sensors and Computer Vision, and Small UAV for Persistent Surveillance.Volume 2 focuses on UAS deployment and applications including UAV-CPSs as a Testbed for New Technologies and a Primer to Industry 5.0, Human-Machine Interface Design, Open Source Software (OSS) and Hardware (OSH), Image Transmission in MIMO-OSTBC System, Image Database, Communications Requirements, Video Streaming, and Communications Links, Multispectral vs Hyperspectral Imaging, Aerial Imaging and Reconstruction of Infrastructures, Deep Learning as an Alternative to Super Resolution Imaging, and Quality of Experience (QoE) and Quality of Service (QoS).

This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem - super-resolution (SR).