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Handbook of Biochips : Integrated Circuits and Systems for Biology and Medicine
This book provides a broad survey of the field of biochips, including fundamentals of microelectronics and biomaterials interaction with various, living tissues, as well as numerous, diverse applications. Although a wide variety of biochips will be described, there will be a focus on those at the brain-machine interface. Analysis is included of the relationship between different categories of biochips and their interactions with the body and coverage includes wireless remote control of biochips and arrays of microelectrodes, based on new biomaterials.
Fuzzy-Neuro Approach to Agent Applications : From the AI Perspective to Modern Ontology
The book provides a full explanation of the concepts and theories of intelligent agents and agent-based systems. Providing a comprehensive theoretical background, the author covers modern artificial intelligence topics such as ontologies, neural networks, chaos theory, fuzzy logics and genetic algorithms. Finally, the author details how the iJADK toolkit (intelligent Java agent development kit for intelligent e-business applications) can be used in the design and implementation phases of real applications.
Evolving Connectionist Systems : The Knowledge Engineering Approach
Evolving Connectionist Systems is aimed at all those interested in developing and using intelligent computational models and systems to solve challenging real world problems in computer science, engineering, bioinformatics and neuroinformatics. The book challenges scientists and practitioners with open questions about future creation of new information models inspired by Nature. This edition includes new methods for adaptive, knowledge-based learning, such as online incremental feature selection, spiking neural networks, transductive neuro-fuzzy inference, adaptive data and model integration, cellular automata and artificial life systems, particle swarm optimisation, ensembles of evolving systems, and quantum inspired neural networks. New applications to gene and protein interaction modelling, brain data analysis and brain model creation, computational neuro-genetic modelling, adaptive speech, image and multimodal recognition, language modelling, adaptive robotics, modelling dynamic financial and socio-economic systems, and ecological modelling, are covered. An important new feature of the book is the attempt to connect different structural and functional levels of a complex, intelligent system, looking for inspiration from functional relationships in natural systems, such as the genetic and the brain activity.
Emergence of Communication and Language
This volume brings together studies from diverse disciplines, showing how they can inform and stimulate each other. It includes work in linguistics, psychology, neuroscience, anthropology and computer science. New empirical work is reported on both human and animal communication, using some novel techniques that have only recently become viable. A principal theme is the importance of studies involving artificial agents, their contribution to the body of knowledge on the emergence of communication and language, and the role of simulations in exploring some of the most significant issues. A number of different synthetic systems are described, demonstrating how communication can emerge in natural and artificial organisms. Theories on the origins of language are supported by computational and robotic experiments. Worldwide contributors to this volume include some of the most influential figures in the field, delivering essential reading for researchers and graduates in the area, as well as providing fascinating insights for a wider readership.
Electronic engineering for neuromedicine
Advances in electronics have revolutionized diagnostic tools and created mobile medicine, touch-sensitive prosthetics, remote surgery, and artificial organs such as hearts, retinas, and bionic skins. This reference text shows the number of ways in which electronic engineering feeds into neuromedicine namely: the modelling and simulation of the brain, providing access to the brain, analysis of the signals and activities of the brain and influencing the function of the brain for therapeutic purposes. The areas of electronic engineering considered are electronic circuits, spectral analysis, filtering of signals, electromagnetic fields and wave propagation. The book is a valuable source to medical students and practitioners as well as electronic engineering and physics students and graduates.
Dynamic brain : From neural spikes to behaviors ; 12th International Summer School on Neural Networks, Erice, Italy, December 5-12, 2007, Revised Lectures
The volume presents 12 thoroughly revised tutorial papers based on lectures given by leading researchers at the 12th International Summer School on Neural Networks in Erice, Italy, in December 2007.
Designing human interface in speech technology
Designing Human Interface in Speech Technology bridges a gap between the needs of the technical engineer and cognitive researchers working in the multidisciplinary area of speech technology applications. The approach is systematic and the focus is on the utility of developing and designing speech related products. Included is coverage of topics such as neuroscience on the multimodal cortex, cognitive theories on multi-task performance, stress and workload, as well as human information process theory and ecological interface design theory for evaluating speech-related human-system interfaces.
Deep Learning to See : Towards New Foundations of Computer Vision
Topics and features: Presents a curiosity-driven approach, posing questions to stimulate readers to design novel computational models of vision Offers a rethinking of computer vision, arguing for an approach based on vision in nature, versus regarding visual signals as collections of images Provides an interdisciplinary commentary, aiming to unify computer vision, machine learning, human vision, and computational neuroscience Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions.
Computer Aided Systems Theory – EUROCAST 2005 ; 10th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 7-11, 2005, Revised Selected Papers
The concept of CAST, computer aided systems Theory, was introduced by F. Pichler of Linz in the late 1980s to include those computer theoretical and practical developments used as tools to solve problems in system science. It was considered as the third component (the other two being CAD and CAM) that would provide for a complete picture of the path from computer and systems sciences to practical developments in science and engineering. Selected papers were published as Springer Lecture Notes in Computer Science vols. 410, 585, 763, 1030, 1333, 1728, 2178 and 2809 and in several special issues of Cybernetics and Systems: an lnternational
Computational Life Sciences ; Vol. 4216 ; 2nd International Symposium, CompLife 2006, Cambridge, UK, September 27-29, 2006, Proceedings
This book constitutes the refereed proceedings of the Second International Symposium on Computational Life Sciences, CompLife 2006. The papers are organized in topical sections on genomics, data mining, molecular simulation, molecular informatics, systems biology, biological networks/metabolism, and computational neuroscience.
Computational intelligence : Research Frontiers : IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, China, June 1-6, 2008, Plenary/Invited Lectures
The book presents the expertise and experiences of leading researchers spanning a diverse spectrum of computational intelligence in the areas of neurocomputing, fuzzy systems, evolutionary computation, and adjacent areas.
Cognitive Systems ; Joint Chinese-German Workshop, Shanghai, China, March 7-11, 2005, Revised Selected Papers
This book organized in topical sections on multimodal human-computer interfaces, neuropsychology and neurocomputing, Chinese-German natural language processing and psycholinguistics, as well as information processing and retrieval from the semantic Web for intelligent applications.
Cognitive engineering : A distributed approach to machine intelligence
Cognitive Engineering: A Distributed Approach to Machine Intelligence explores the design issues of intelligent engineering systems. Beginning with the foundations of psychological modeling of the human mind, the main emphasis is given to parallel and distributed realization of intelligent models for application in reasoning, learning, planning and multi-agent co-ordination problems. The last two chapters provide case studies on human-mood detection and control, and behavioral co-operation of mobile robots. This is the first comprehensive text of its kind, bridging the gap between Cognitive Science and Cognitive Systems Engineering. Each chapter includes plenty of numerical examples and exercises with sufficient hints, so that the reader can solve the exercises on their own. Computer simulations are also included in most chapters to give a clear idea about the application of the algorithms undertaken in the book. In addition, mathematical analysis on convergence and stability of the neuro-fuzzy models will enable the reader to pursue their research career in cognitive engineering.
Mathematical modeling of the human brain : From magnetic resonance images to finite element simulation
This book bridges common tools in medical imaging and neuroscience with the numerical solution of brain modelling PDEs. The connection between these areas is established through the use of two existing tools, FreeSurfer and FEniCS, and one novel tool, the SVM-Tk, developed for this book. The reader will learn the basics of magnetic resonance imaging and quickly proceed to generating their first FEniCS brain meshes from T1-weighted images.
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine learning for brain disorders
Organized into five parts. Part One presents the fundamentals of ML. Part Two looks at the main types of data used to characterize brain disorders, including clinical assessments, neuroimaging, electro- and magnetoencephalography, genetics and omics data, electronic health records, mobile devices, connected objects and sensors. Part Three covers the core methodologies of ML in brain disorders and the latest techniques used to study them. Part Four is dedicated to validation and datasets, and Part Five discusses applications of ML to various neurological and psychiatric disorders.
Knowledge-Based Intelligent Information and Engineering Systems ; 12th International Conference, KES 2008, Zagreb, Croatia, September 3-5, 2008, Proceedings, Part I
The 316 revised papers presented were carefully reviewed and selected. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the first volume are artificial neural networks and connectionists systems; fuzzy and neuro-fuzzy systems; evolutionary computation; machine learning and classical AI; agent systems; knowledge based and expert systems; intelligent vision and image processing; knowledge management, ontologies, and data mining; Web intelligence, text and multimedia mining and retrieval; and intelligent robotics and control.
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ; 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I
The content of thebook covers the current state-of-the-art literature on federated learning applications for cancer research and Vclinical oncology analysis, as well as an overview of the deep learning approaches improving the current standard of care for brain lesions and current neuroimaging challenges. It is also focusing on the accepted BrainLes workshop submissions, is to provide an overview of new advances of medical image analysis in all the aforementioned brain pathologies. It brings together researchers from the medical image analysis domain, neurologists, and radiologists working on at least one of these diseases. The aim is to consider neuroimaging biomarkers used for one disease applied to the other diseases.
Brain-inspired computing ; 4th International Workshop, BrainComp 2019, Cetraro, Italy, July 15–19, 2019, Revised Selected Papers
The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
