"This book provides interdisciplinary research that evaluates the performance of machine visual models and systems in comparison to biological systems, blending the ideas of current scientific knowledge and biological vision"--
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.
As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and volume, the need to process and interpret all the data has made image processing and computer vision increasingly important. Sources of data that have to be routinely dealt with today's applications include video transmission, wireless communication, automatic fingerprint processing, massive databanks, non-weary and accurate automatic airport screening, robust night vision, just to name a few. Multidisciplinary inputs from other disciplines such as physics, computational neuroscience, cognitive science, mathematics, and biology will have a fundamental impact in the progress of imaging and vision sciences. One of the advantages of the study of biological organisms is to devise very different type of computational paradigms by implementing a neural network with a high degree of local connectivity. This is a comprehensive and rigorous reference in the area of biologically motivated vision sensors. The study of biologically visual systems can be considered as a two way avenue. On the one hand, biological organisms can provide a source of inspiration for new computational efficient and robust vision models and on the other hand machine vision approaches can provide new insights for understanding biological visual systems. Along the different chapters, this book covers a wide range of topics from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. The last two sections of the book provide an overview of a few representative applications and current state of the art of the research in this area. This makes it a valuable book for graduate, Master, PhD students and also researchers in the field.
"This book provides the reader with a concrete understanding of basic principles and pitfalls for 3-D capturing, highlighting stereoscopic imaging systems including holography"--
The field of mechatronics integrates modern engineering science and technologies with new ways of thinking, enhancing the design of products and manufacturing processes. This synergy enables the creation and evolution of new intelligent human-oriented machines. The Handbook of Research on Advancements in Robotics and Mechatronics presents new findings, practices, technological innovations, and theoretical perspectives on the the latest advancements in the field of mechanical engineering. This book is of great use to engineers and scientists, students, researchers, and practitioners looking to develop autonomous and smart products and systems for meeting todays challenges.
The two volume set LNCS 8047 and 8048 constitutes the refereed proceedings of the 15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013, held in York, UK, in August 2013. The 142 papers presented were carefully reviewed and selected from 243 submissions. The scope of the conference spans the following areas: 3D TV, biometrics, color and texture, document analysis, graph-based methods, image and video indexing and database retrieval, image and video processing, image-based modeling, kernel methods, medical imaging, mobile multimedia, model-based vision approaches, motion analysis, natural computation for digital imagery, segmentation and grouping, and shape representation and analysis.
This book constitutes the thoroughly refereed post-conference proceedings of the 10th International Workshop on Graphics Recognition, GREC 2013, held in Bethlehem, PA, USA, in August 2013. The 20 revised full papers presented were carefully reviewed and selected from 32 initial submissions. Graphics recognition is a subfield of document image analysis that deals with graphical entities in engineering drawings, sketches, maps, architectural plans, musical scores, mathematical notation, tables, and diagrams. Accordingly the conference papers are organized in 5 topical sessions on symbol spotting and retrieval, graphics recognition in context, structural and perceptual based approaches, low level processing, and performance evaluation and ground truthing.
These three volumes (CCIS 442, 443, 444) constitute the proceedings of the 15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, held in Montpellier, France, July 15-19, 2014. The 180 revised full papers presented together with five invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on uncertainty and imprecision on the web of data; decision support and uncertainty management in agri-environment; fuzzy implications; clustering; fuzzy measures and integrals; non-classical logics; data analysis; real-world applications; aggregation; probabilistic networks; recommendation systems and social networks; fuzzy systems; fuzzy logic in boolean framework; management of uncertainty in social networks; from different to same, from imitation to analogy; soft computing and sensory analysis; database systems; fuzzy set theory; measurement and sensory information; aggregation; formal methods for vagueness and uncertainty in a many-valued realm; graduality; preferences; uncertainty management in machine learning; philosophy and history of soft computing; soft computing and sensory analysis; similarity analysis; fuzzy logic, formal concept analysis and rough set; intelligent databases and information systems; theory of evidence; aggregation functions; big data - the role of fuzzy methods; imprecise probabilities: from foundations to applications; multinomial logistic regression on Markov chains for crop rotation modelling; intelligent measurement and control for nonlinear systems.
This book gathers authoritative contributions in the field of Soft Computing. Based on selected papers presented at the 7th World Conference on Soft Computing, which was held on May 29–31, 2018, in Baku, Azerbaijan, it describes new theoretical advances, as well as cutting-edge methods and applications. New theories and algorithms in fuzzy logic, cognitive modeling, graph theory and metaheuristics are discussed, and applications in data mining, social networks, control and robotics, geoscience, biomedicine and industrial management are described. This book offers a timely, broad snapshot of recent developments, including thought-provoking trends and challenges that are yielding new research directions in the diverse areas of Soft Computing.
There is now strong evidence demonstrating that the brain simulates action and other functions. Such action simulation can be evoked through conscious mental rehearsal of movement or imagery, but also through passive action observation watching movements in others. Furthermore, there is evidence to suggest that mental rehearsal of movement, or mental practice, can produce improvements normally attributed to practising actual movements. It is currently assumed that such improvements are due to neural activation associated with action simulation. However the neuroscience of mental practice efficacy is still poorly understood. The aim of this research topic is to clarify the underlying mechanisms of mental practice, bringing evidence from cognitive neuroscience, experimental neuropsychology, sport and movement science, and clinical neurology. It also attempts to address confusion regarding the concepts of imagery and observation, which has hampered the progression of mental practice research both scientifically and applied. As well as reviews, theoretical, and position articles, this research topic includes original neuroimaging, experimental, and patient research addressing, among others, the following issues. Neuroimaging studies provide strong evidence for action simulation, but the link to behavioural change and functional outcome is weak. What is the evidence that mental practice efficacy is driven by neuroplasticity processes evoked by action simulation? This research topic includes contributions on neural correlates and behaviour with regards to imagery and action observation. Much of the mental practice efficacy evidence comes from longstanding research within sport science. However, what does mental practice entail in these contexts, and to what extent is it compatible with the cognitive neuroscience perspective of action simulation? This research topic will include contributions that consider both evidence and concepts with regards to imagery and action observation, in an attempt to build an interdisciplinary consensus on the nature and application of mental practice. Mental practice is perceived as a promising motor rehabilitation technique, but critically there is lack of clarity or consensus on what mental practice treatment should entail. It is also not clear what are the most appropriate outcomes to measure imagery ability and cognitive or behavioural change following mental practice. A further important issue that needs consideration as part of this research topic is dosage, as it is currently unclear how much mental practice is appropriate and whether this depends on patient variables such as age, cognitive functioning, motor function, or pathophysiology.