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Visual Data Mining : Theory, Techniques and Tools for Visual Analytics
The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.
Variational, geometric, and level set methods in computer vision ; 3rd International Workshop, VLSM 2005, Beijing, China, October 16, 2005, Proceedings
Mathematical methods has been a dominant research path in computational vision leading to a number of areas like ?ltering, segmentation, motion analysis and stereo reconstruction.
Transactions on Rough Sets V
Volume V of the Transactions on Rough Sets (TRS) is dedicated to the monu-mental life and work of Zdzis law Pawlak1. During the past 35 years, This volume continues the traditionbegun with earlier volumes of the TRS series and introduces a number of newadvances in the foundations and application of rough sets. These advances haveprofound implications in a number of research areas such as adaptive learning,approximate reasoning and belief systems, approximation spaces, Boolean rea-soning, classification methods, classifiers, concept analysis, data mining, decisionlogic, decision rule importance measures, digital image processing, recognitionof emotionally-charged gestures in animations, flow graphs, Kansei engineering,movie sound track restoration, multicriteria decision analysis, relational informa-tion systems, rough-fuzzy sets, rough measures, signal processing, variable pre-cision rough set model, and video retrieval.
Spatial Analysis and GeoComputation : Selected Essays
Spatial analysis has been in existence for a long time. More recently, GeoComputation - a new computationally intensive paradigm - is changing research practice in spatial analysis. Coupled with improvements in data availability and increases in computer memory and speed, novel perspectives and techniques from the field of computational intelligence give rise to new types of geocomputational concepts, models, and techniques in spatial analysis. This volume contains selected essays of Manfred M. Fischer in the field of spatial analysis from the perspective of GeoComputation. The volume is structured in four parts. The first sets the context by dealing with broad issues related with spatial analysis and the role of GIS. The second relates to computational intelligence technologies such as neural networks that provide a new style of performing spatial modelling and analysis tasks in geography and other spatial sciences. The third part provides the theoretical framework required and displays the efficient use of various adaptive pattern classifiers in remote sensing environments. The final part outlines the latest, most significant developments in neural spatial interaction modelling.
Soft Computing in Industrial Applications : Recent and Emerging Methods and Techniques
Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.
Sensor systems for gesture recognition
Gesture recognition (GR) aims to interpret human gestures, having an impact on a number of different application fields. This Special Issue is devoted to describing and examining up-to-date technologies to measure gestures, algorithms to interpret data, and applications related to GR. These technologies involve camera-based systems (e.g., ground truth system, GTS; Azura Kinect), wearable sensors (e.g., inertial measurement units, IMUs; micro electro-mechanical systems, MEMS; angular displacement sensors, ADS; resistive flex sensors, RFSs), electromagnetic field measurements (e.g., leap motion sensor), acoustic-based inputs (e.g., microphone, stethoscope), radar systems (e.g., continuous wave), and tactile sensors (e.g., pressure sensitive transistors). Data interpretations are detailed by means of classifiers (e.g., neural networks, NN; convolutional neural network, CNN; hidden Markov models, HMM; and k-nearest neighbors, kNN).
Scale Space and Variational Methods in Computer Vision ; 1st International Conference, SSVM 2007, Ischia, Italy, May 30 - June 2, 2007, Proceedings
Constitutes the refereed proceedings of the First International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2007. This book introduces topical sections on scale space and features extraction, image enhancement and reconstruction, image segmentation and visual grouping, motion analysis, and optical flow.
Rule-Based Evolutionary Online Learning Systems : A Principled Approach to LCS Analysis and Design
This book offers a comprehensive introduction to learning classifier systems (LCS) – or more generally, rule-based evolutionary online learning systems. LCSs learn interactively – much like a neural network – but with an increased adaptivity and flexibility.
Progress in pattern recognition, image analysis and applications ; 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Havana, Cuba, September 9-12, 2008. Proceedings
This book is organized in topical sections on signal analysis for characterization and filtering, analysis of shape and texture, analysis of speech and language, data mining, clustering of images and documents, statistical pattern recognition, classification and description of objects, classification and edition, geometric image analysis, neural networks, computer vision, image coding, associative memories and neural networks, interpolation and video tracking, images analysis, music and speech analysis, as well as classifier combination and document filtering.
Probabilistic Inductive Logic Programming : Theory and Applications
One of the key open questions within arti?cial intelligence is how to combine probability and logic with learning. This question is getting an increased tentioninseveral disciplines suchas knowledg erepresentation, reasoningabout uncertainty, data mining, and machine learning simulateously,This book providesan introduction to this ?eld with an emphasison those methods based on logic programming principles. The book is also the main result of the successful European ISTFET projectno.FP6-508861on Applition of ProbabilisticInductive Logic Programming (APRILII,2004-2007).It was concerned with theory, implementation sand applications of probabilisticinductivelogic programming.
Pattern Recognition and Image Analysis ; 3rd Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part II
Constitutes the refereed proceedings of the Third Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007, held in Girona, Spain in June 2007. This title presents 48 revised full papers and 108 revised poster papers together with 3 invited talks that were reviewed and selected from 328 submissions.
Pattern Recognition and Image Analysis ; 3rd Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I
Part of a two-volume set, this book constitutes the refereed proceedings of the Third Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007, held in Girona, Spain in June 2007. It covers pattern recognition, human language technology, special architectures and industrial applications, motion analysis, and image analysis.
Partial Covers, Reducts and Decision Rules in Rough Sets : Theory and Applications
Devoted to theoretical and experimental study of partial reducts and partial decision rules on the basis of the study of partial covers. The use of partial (approximate) reducts and decision rules instead of exact ones allows us to obtain more compact description of knowledge contained in decision tables, and to design more precise classifiers. Algorithms for construction of partial reducts and partial decision rules, bounds on minimal complexity of partial reducts and decision rules, and algorithms for construction of the set of all partial reducts and the set of all irreducible partial decision rules are considered. The book includes a discussion on the results of numerous experiments with randomly generated and real-life decision tables. These results show that partial reducts and decision rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction.
Parallel Problem Solving from Nature - PPSN IX ; 9th International Conference, Reykjavik, Iceland, September 9-13, 2006, Proceedings
We received 255 paper submissions this year. After an extensive peer review process involving more than 1000 reviews, the programme committee selected the top 106 papers for inclusion in this volume and, of course, for presentation at the conference. This represents an acceptance rate of 42%. The papers included in this volume cover a wide range of topics, from e- lutionary computation to swarm intelligence and from bio-inspired computing to real-world applications. They represent some of the latest and best research in evolutionary and natural computation. Following the PPSN tradition, all - pers at PPSN IX were presented as posters. There were 7 sessions: each session consisting of around 15 papers. For each session, we covered as wide a range of topics as possible so that participants with di?erent interests could ?nd some relevant papers in every session.
Multiple Classifier Systems ; 7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings
These proceedings are a record of the Multiple Classifier Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic.
Multiple Classifier Systems ; 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings
Constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005. This book contains papers that are organized in topical sections on boosting, combination methods, performance analysis, and applications. They exemplify the advances in the theory and applications of multiple classifier systems
Multiple Classifier Systems ; 2nd International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule.
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 data engineering and automated Learning - IDEAL 2006 ; 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings
This volume of Lecture Notes in Computer Science contains accepted - pers presented at IDEAL 2006 held at the University of Burgos, Spain, during, September 20–23, 2006. The conference received 557 submissions from over 40 countriesaroundtheworld,whichweresubsequentlyrefereedbytheProgramme Committeeandmanyadditionalreviewers.Afterrigorousreview,170top-quality papers were accepted and included in the proceedings. The acceptance rate was only 30%, which ensured an extremely high-quality standard of the conference. The buoyant number of submitted papers is a clear proof of the vitality and increased importance of the ?elds related to IDEAL, and is also an indication of the rising popularity of the IDEAL conferences.
Information security and privacy ; 13th Australasian Conference, ACISP 2008, Wollongong, Australia, July 7-9, 2008. Proceedings
This book constitutes the refereed proceedings of the 13th Australasian Conference on Information Security and Privacy, ACISP 2008, held in Wollongong, Australia, in July 2008.The 33 revised full papers presented were carefully reviewed and selected from 111 submissions. The papers cover a range of topics in information security, including authentication, key management, public key cryptography, privacy, anonymity, secure communication, ciphers, network security, elliptic curves, hash functions, and database security.
