الصفحة 1
الصفحة 1
New trends in computational vision and bio-inspired computing : Selected works presented at the ICCVBIC 2018, Coimbatore, India
Gathers selected, peer-reviewed original contributions presented at the International Conference on Computational Vision and Bio-inspired Computing (ICCVBIC) conference which was held in Coimbatore, India, on November 29-30, 2018. The works included here offer a rich and diverse sampling of recent developments in the fields of Computational Vision, Fuzzy, Image Processing and Bio-inspired Computing. The topics covered include computer vision; cryptography and digital privacy; machine learning and artificial neural networks; genetic algorithms and computational intelligence; the Internet of Things; and biometric systems, to name but a few. The applications discussed range from security, healthcare and epidemic control to urban computing, agriculture and robotics.
Neural Networks : Computational Models and Applications
Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.
Neural Nets ; 16th Italian Workshop on Neural Nets, WIRN 2005, International workshop on natural and artificial immune systems, NAIS 2005, Vietri sul Mare, Italy, June 8-11, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 16th Italian Workshop on Neural Nets, WIRN 2005, as well as the satellite International Workshop on Natural and Artificial Immune Systems, NAIS 2005, held in Vietri sul Mare, Italy in June 2005. The 41 revised papers presented together with a lecture by the winner of the Premio Caianiello award were carefully reviewed and improved during two rounds of selection and refereeing.
Nature Inspired Problem-Solving Methods in Knowledge Engineering ; 2nd International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2007, La Manga del Mar Menor, Spain, June 18-21, 2007, Proceedings, Part II
The second of a two-volume set, this book constitutes the refereed proceedings of the Second International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2007, held in La Manga del Mar Menor, Spain in June 2007.
Multimedia Services in Intelligent Environments : Advanced Tools and Methodologies
This book presents a sample of recent research results in multimedia services. Besides the introductory chapter, this book includes fourteen additional chapters. Nine of these chapters cover various aspects of data processing in multimedia services in intelligent environments, such as storage, recognition and classification, transmission, information retrieval, and information securing. Four additional chapters present multimedia services in noise and hearing monitoring and measuring, augmented reality, automated lecture rooms and rights management and licensing. Finally, the last chapter is devoted to an intelligent recommender service in scientific digital libraries.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Modelling, Monitoring and Diagnostic Techniques for Fluid Power Systems
Modelling, Monitoring and Diagnostic Techniques for Fluid Power Systems covers the background theory of fluid power and indicates the range of concepts necessary for a modern approach to condition monitoring and fault diagnosis in a readable and understandable fashion. The theory is constantly leavened by 15 years' worth of practical measurements by the author, working in association with major fluid power companies, and real industrial case studies – hot-strip-mill monitoring in conjunction with Corus p.l.c. being just one example. Comprising four parts, it provides: • an introduction to component behaviour. • a guide to the modelling methods employed for circuit analysis. • methods for doing condition monitoring. • common faults and breakdowns.
Modeling Solar Radiation at the Earth’s Surface : Recent Advances
Solar radiation data is important for a wide range of applications, e.g. in engineering, agriculture, health sector, and in many fields of the natural sciences. A few examples showing the diversity of applications may include: architecture and building design e.g. air conditioning and cooling systems; solar heating system design and use; solar power generation; weather and climate prediction models; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control; skin cancer research.
Mobile Robots : The Evolutionary Approach
The design and control of autonomous intelligent mobile robotic systems operating in unstructured changing environments includes many objective difficulties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to fit in their environments. The application and use of bio-inspired and intelligent techniques such as reinforcement learning, artificial neural networks, evolutionary computation and so forth in the design and improvement of robot designs is an emergent research topic. Researchers have obtained robots that display an amazing slew of behaviours and perform a multitude of tasks. These include perception of environment, planning and navigation in rough terrain, pushing boxes, negotiating an obstacle course, etc.
Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Methods and Procedures for the Verification and Validation of Artificial Neural Networks is the culmination of the first steps in that research. This volume introduces some of the more promising methods and techniques used for the verification and validation (V&V) of neural networks and adaptive systems. A comprehensive guide to performing V&V on neural network systems, aligned with the IEEE Standard for Software Verification and Validation, will follow this book. The NASA IV&V and the Institute for Scientific Research, Inc. are working to be at the forefront of software safety and assurance for neural network and adaptive systems.
Mechanisms, Symbols, and Models Underlying Cognition ; 1st International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I
Constitute the refereed proceedings of the First International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2005. This two-volume set contains papers that are related with the conceptual developments in the fields of Neurophysiology and cognitive science, and also to bioinspired programming strategies.
Intelligent information processing and web mining ; Proceedings of the International IIS : IIPWM´06 Conference held in Ustron, Poland, June 19-22, 2006
This volume contains selected papers, presented at the international conference on Intelligent Information Processing and Web Mining Conference IIS:IIPWM'06, organized in Ustro« (Poland) on June 19-22nd, 2006. The submitted papers cover new computing paradigms, among others in biologically motivated methods, advanced data analysis, new machine learning paradigms, natural language processing, new optimization technologies, applied data mining using statistical and non-standard approaches.
Intelligent data engineering and automated Learning - IDEAL 2008 ; 9th International Conference Daejeon, South Korea, November 2-5, 2008 Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2008, held in Daejeon, Korea, in November 2008.The 56 revised full papers presented together with 10 invited papers were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers are organized in topical sections on learning and information processing, data mining and information management, bioinformatics and neuroinformatics, agents and distributed systems, as well as financial engineering and modeling.
Intelligent Computing in Engineering and Architecture ; 13th EG-ICE Workshop 2006, Ascona, Switzerland, June 25-30, 2006, Revised Selected Papers
Providing computer support for tasks in civil engineering and architecture is hard. Projects can be complex, long and costly. Firms that contribute to design, construction and maintenance are often worth less than the value of their projects. Everyone in the field is justifiably risk adverse. Contextual variables have a strong influence making generalization difficult. The product life cycle may exceed one hundred years and functional requirements may evolve during the service life. It is therefore no wonder that practitioners in this area have been so reluctant to adopt advanced computing systems. After decades of research and industrial pilot projects, advanced computing s- tems are now being recognized by many leading practitioners to be strategically - portant for the future profitability of firms involved in engineering and architecture. Engineers and architects with advanced computing knowledge are hired quickly in the market place. Closer collaboration between research and practice is leading to more comprehensive validation processes for new research ideas. This is feeding devel- ment of more useful systems, thus accelerating progress. These are exciting times. th This volume contains papers that were presented at the 13 Workshop of the Eu- pean Group for Intelligent Computing in Engineering. Over five days, 70 participants from around the world listened to 59 paper presentations in a single session format.
Intelligent Computing Everywhere
Intelligent Computing Everywhere investigates the relevance and relationship artificial intelligence maintains with "modern strands of computing" i.e. pervasive computing and ambient intelligence, bioinformatics, neuroinformatics, computing and the mind, non-classical computing and novel computing models, as well as DNA computing and quantum computing.
High performance computational science and engineering : IFIP TC5 Workshop on High Performance Computational Science and Engineering (HPCSE), World Computer Congress, August 22-27, 2004, Toulouse, France
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research. The principal aim of the IFIP series is to encourage education and the dissemination and exchange of information about all aspects of computing.
Hebbian Learning and Negative Feedback Networks
This book is the outcome of a decade’s research into a speci?c architecture and associated learning mechanism for an arti?cial neural network: the - chitecture involves negative feedback and the learning mechanism is simple Hebbian learning. The research began with my own thesis at the University of Strathclyde, Scotland, under Professor Douglas McGregor which culminated with me being awarded a PhD in 1995 [52], the title of which was “Negative Feedback as an Organising Principle for Arti?cial Neural Networks”. Naturally enough, having established this theme, when I began to sup- vise PhD students of my own, we continued to develop this concept and this book owes much to the research and theses of these students at the Applied Computational Intelligence Research Unit in the University of Paisley . All of Chapters 3 to 8 deal with single stream arti?cial neural networks.
Handbook on Decision Support Systems 1 : Basic Themes
Decision support systems have experienced a marked increase in attention and importance over the past 25 years. The aim of this book is to survey the decision support system (DSS) field – covering both developed territory and emergent frontiers. It will give the reader a clear understanding of fundamental DSS concepts, methods, technologies, trends, and issues. It will serve as a basic reference work for DSS research, practice, and instruction. To achieve these goals, the book has been designed according to a ten-part structure, divided in two volumes with chapters authored by well-known, well-versed scholars and practitioners from the DSS community.
Handbook of Nature-Inspired and Innovative Computing : Integrating Classical Models with Emerging Technologies
This comprehensive handbook, the first of its kind to address the connection between nature-inspired and traditional computational paradigms, is a repository of case studies dealing with different problems in computing and solutions to these problems based on nature-inspired paradigms. The "Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies" is an essential compilation of models, methods, and algorithms for researchers, professionals, and advanced-level students working in all areas of computer science, IT, biocomputing, and network engineering.
Global optimization ; Vol. 85 : Scientific and engineering case studies
Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of global optimization (GO) is to find the best possible solution of multiextremal problems. Global Optimization: Selected Case Studies illustrates the applicability of GO modeling techniques and solution strategies to real-world problems.The contributed chapters cover a broad range of applications from agroecosystem management, assembly line design, bioinformatics, biophysics, black box systems optimization, cellular mobile network design, chemical process optimization, chemical product design, composite structure design, computational modeling of atomic and molecular structures, controller design for induction motors, electrical engineering design, feeding strategies in animal husbandry, the inverse position problem in kinematics, laser design, learning in neural nets, mechanical engineering design, numerical solution of equations, radiotherapy planning, robot design, and satellite data analysis. The solution strategies discussed encompass a range of practically viable methods, including both theoretically rigorous and heuristic approaches.
