João Manuel R. S. Tavares – författare

This book reports on timely research at the interface between biomedical engineering and intelligence technologies applied to biology and healthcare. It covers cutting-edge methods applied to biomechanics and robotics, EEG time series analysis, blood glucose prediction models, among others. It includes ten chapters, which were selected upon a rigorous peer-review process and presented at the 1st World Thematic Conference - Biomedical Engineering and Computational Intelligence, BIOCOM 2018, held in London, United Kingdom, during October 30–31, 2018.

This book gathers selected, extended and revised contributions to the 15th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE2018), and the 3rd Conference on Imaging and Visualization, which took place on 26-29 March, 2018, in Lisbon, Portugal. The respective chapters highlight cutting-edge methods, e.g. new algorithms, image analysis techniques, and multibody modeling methods; and new findings obtained by applying them in biological and/or medical contexts. Original numerical studies, Monte Carlo simulations, FEM analyses and reaction-diffusion models are described in detail, together with intriguing new applications.

The book offers a timely source of information for biologists, engineers, applied mathematicians and clinical researchers working on multidisciplinary projects, and is also intended to foster closer collaboration between these groups.

This book gathers full papers presented at the VipIMAGE 2019—VII ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing—held on October 16-18, 2019, in Porto, Portugal. It discusses cutting-edge methods, findings, and applications related to 3D vision, bio- and medical imaging, computer-aided diagnosis, image enhancement, image processing and analysis, virtual reality, and also describes in detail advanced image analysis techniques, such as image segmentation and feature selection, as well as statistical and geometrical modeling. The book provides both researchers and professionals with extensive and timely insights into advanced imaging techniques for various application purposes.

This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to process a large number of data streams by implementing new computing paradigms has been demonstrated in numerous studies incorporating computational techniques in the emerging bio-inspired models.

The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization, and big data modeling and management, that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems, and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications. 

This book emphasizes the emerging building block of image processing domain, which is known as capsule networks for performing deep image recognition and processing for next-generation imaging science. Recent years have witnessed the continuous development of technologies and methodologies related to image processing, analysis and 3D modeling which have been implemented in the field of computer and image vision. The significant development of these technologies has led to an efficient solution called capsule networks [CapsNet] to solve the intricate challenges in recognizing complex image poses, visual tasks, and object deformation. Moreover, the breakneck growth of computation complexities and computing efficiency has initiated the significant developments of the effective and sophisticated capsule network algorithms and artificial intelligence [AI] tools into existence. 

The main contribution of this book is to explain and summarize the significant state-of-the-art research advances in the areas of capsule network [CapsNet] algorithms and architectures with real-time implications in the areas of image detection, remote sensing, biomedical image analysis, computer communications, machine vision, Internet of things, and data analytics techniques. 

This book includes the papers presented in 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021]. In this digital era, image processing plays a significant role in wide range of real-time applications like sensing, automation, health care, industries etc. Today, with many technological advances, many state-of-the-art techniques are integrated with image processing domain to enhance its adaptiveness, reliability, accuracy and efficiency. With the advent of intelligent technologies like machine learning especially deep learning, the imaging system can make decisions more and more accurately. Moreover, the application of deep learning will also help to identify the hidden information in volumetric images. Nevertheless, capsule network, a type of deep neural network, is revolutionizing the image processing domain; it is still in a research and development phase. In this perspective, this book includes the state-of-the-art research works that integrate intelligent techniques with image processing models, and also, it reports the recent advancements in image processing techniques. Also, this book includes the novel tools and techniques for deploying real-time image processing applications.

The chapters will briefly discuss about the intelligent image processing technologies, which leverage an authoritative and detailed representation by delivering an enhanced image and video recognition and adaptive processing mechanisms, which may clearly define the image and the family of image processing techniques and applications that are closely related to the humanistic way of thinking.

The book presents studies related to artificial intelligence (AI) and its applications to process and analyze data and big data to create machines or software that can better understand business behavior, industry activities, and human health. The studies were presented at “The 2021 International Conference on Artificial Intelligence and Big Data in Digital Era” (ICABDE 2021), which was held in Ho Chi Minh City, Vietnam, during December 18-19, 2021.

“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human”

—Alan Turing

This book gathers selected, extended and revised contributions to the 17th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering and the 5th Conference on Imaging and Visualization (CMBBE 2021), held online on September 7-9, 2021, from Bonn, Germany. It reports on cutting-edge models, algorithms and imaging techniques for studying cells, tissues and organs in normal and pathological conditions. It covers numerical and machine learning methods, finite element modeling and virtual reality techniques, applied to understand biomechanics of movement, fluid and soft tissue biomechanics. It also reports on related advances in rehabilitation, surgery and diagnosis. All in all, this book offers a timely snapshot of the latest research and current challenges at the interface between biomedical engineering, computational biomechanics and biological imaging. Thus, it is expected to provide a source of inspiration for future research and cross-disciplinary collaborations.

This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.

Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.