This work provides a review of biological networks as a model for analysis, presenting and discussing a number of illuminating analyses. Biological networks are an effective model for providing insights about biological mechanisms. Networks with different characteristics are employed for representing different scenarios. This powerful model allows analysts to perform many kinds of analyses which can be mined to provide interesting information about underlying biological behaviors. The text also covers techniques for discovering exceptional patterns, such as a pattern accounting for local similarities and also collaborative effects involving interactions between multiple actors (for example genes). Among these exceptional patterns, of particular interest are discriminative patterns, namely those which are able to discriminate between two input populations (for example healthy/unhealthy samples). In addition, the work includes a discussion on the most recent proposal on discovering discriminative patterns, in which there is a labeled network for each sample, resulting in a database of networks representing a sample set. This enables the analyst to achieve a much finer analysis than with traditional techniques, which are only able to consider an aggregated network of each population.

This book constitutes the refereed proceedings of the 6th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2016, held in Sidi Bou Said Village, Tunisia, in October 2016. The 9 revised full papers and 7 revised short papers presented were carefully reviewed and selected from 23 submissions. The papers are organized in topical sections on 3D shape registration and comparison; face analysis and recognition; video and motion analysis; 2D shape analysis.

This book presents a systematic study of visual pattern discovery, from unsupervised to semi-supervised manner approaches, and from dealing with a single feature to multiple types of features. Furthermore, it discusses the potential applications of discovering visual patterns for visual data analytics, including visual search, object and scene recognition. It is intended as a reference book for advanced undergraduates or postgraduate students who are interested in visual data analytics, enabling them to quickly access the research world and acquire a systematic methodology rather than a few isolated techniques to analyze visual data with large variations. It is also inspiring for researchers working in computer vision and pattern recognition fields. Basic knowledge of linear algebra, computer vision and pattern recognition would be helpful to readers.

This volume presents 70 carefully selected papers from a major joint event: the 8th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) and the 8th International Conference on Computational Aspects of Social Networks (CASoN 2016). SoCPaR-CASoN 2016, which was organized by the Machine Intelligence Research Labs (MIR Labs), USA and Vellore Institute of Technology (VIT), India and held at the VIT on December 19-21, 2016. It brings together researchers and practitioners from academia and industry to share their experiences and exchange new ideas on all interdisciplinary areas of soft computing and pattern recognition, as well as intelligent methods applied to social networks. This book is a valuable resource for practicing engineers/scientists and researchers working in the field of soft computing, pattern recognition and social networks.

This book constitutes the refereed proceedings of the 11th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2016, held in Beijing, China in July 2016. The 27 papers presented were carefully reviewed and selected from 69 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications.

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.

This book presents the first paradigm of social multimedia computing completely from the user perspective. Different from traditional multimedia and web multimedia computing which are content-centric, social multimedia computing rises under the participatory Web2.0 and is essentially user-centric. The goal of this book is to emphasize the user factor in facilitating effective solutions towards both multimedia content analysis, user modeling and customized user services. Advanced topics like cross-network social multimedia computing are also introduced as extensions and potential directions along this research line.

This book constitutes the refereed proceedings of the 4th Chinese Conference, IVS 2016, held in Beijing, China, in October 2016. The 19 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on low-level preprocessing, surveillance systems; tracking, robotics; identification, detection, recognition; behavior, activities, crowd analysis.

The two-volume set CCIS 662 and CCIS 663 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition, CCPR 2016, held in Chengdu, China, in November 2016.The 121 revised papers presented in two volumes were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on robotics; computer vision; basic theory of pattern recognition; image and video processing; speech and language; emotion recognition.

This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015. The 36 revised full papers presented together with the abstracts of three invited talks and two tutorials were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on industrial-engineering applications of ANN; bioinformatics; intelligent medical modeling; life-earth sciences intelligent modeling; learning-algorithms; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial mapping; classification; financial intelligent modeling; echo state networks.

Traditional Pattern Recognition (PR) and Computer Vision (CV) technologies have mainly focused on full automation, even though full automation often proves elusive or unnatural in many applications, where the technology is expected to assist rather than replace the human agents. However, not all the problems can be automatically solved being the human interaction the only way to tackle those applications. Recently, multimodal human interaction has become an important field of increasing interest in the research community. Advanced man-machine interfaces with high cognitive capabilities are a hot research topic that aims at solving challenging problems in image and video applications. Actually, the idea of computer interactive systems was already proposed on the early stages of computer science. Nowadays, the ubiquity of image sensors together with the ever-increasing computing performance has open new and challenging opportunities for research in multimodal human interaction. This book aims to show how existing PR and CV technologies can naturally evolve using this new paradigm. The chapters of this book show different successful case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.

This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016. The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.

The heart of pattern recognition concepts, methods and applications are explored in this textbook, using statistical, syntactic and neural approaches. The book clearly demonstrates the similarities and differences among the three approaches and each chapter provides the reader with examples and pertinent literature for a more in-depth study of specific topics.

This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key research undertaken in speech coding, speech enhancement, speech recognition, emotion recognition and speaker diarization are also presented, along with recent advances and new paradigms in these areas.

Texture accounts for an important part of the realism of simulated experiences, and it is most certainly true during tactile interaction. We usually experience roughness by running our fingers onto the explored surface. The perception of this fine texture is mediated by the vibrations generated by the encounters of the skin and the asperities of the surfaces. Reproduction of Tactual Textures presents factors that contribute to the mechanics of the interaction between a bare finger and a surface with a view to their artificial reproduction. It discusses the recording and reproduction of tactual textures, and analyses a case study of the development of a device able to record the vibratory signal from a fingertip sliding over a textured surface. The same device is then used in a reverse way to render those previously measured signals to the user's fingertip. These developments open new questions about the biomechanical properties of the skin and their relation to perception. The second half of Reproduction of Tactual Textures focuses on the implication of the dynamic parameters of the skin onto rendering performance, and it concludes with a study on the important features that are present in the vibratory signal and their relation to texture perception. This state-of-the-art volume highlights the importance of the mechanics and biomechanics during the haptic exploration of surfaces and their possible contribution to perception. Collectively, the findings reported are pertinent to many applications, including robotic perception and the design of effective virtual reality systems.

This authoritative collection introduces the reader to the state of the art in iris recognition technology. Topics and features: with a Foreword by the "father of iris recognition," Professor John Daugman of Cambridge University; presents work from an international selection of preeminent researchers, reflecting the uses of iris recognition in many different social contexts; provides viewpoints from researchers in government, industry and academia, highlighting how iris recognition is both a thriving industry and an active research area; surveys previous developments in the field, and covers topics ranging from the low-level (e.g., physics of iris image acquisition) to the high level (e.g., alternative non-Daugman approaches to iris matching); introduces many active and open areas of research in iris recognition, including cross-wavelength matching and iris template aging. This book is an essential resource for anyone wishing to improve their understanding of iris recognition technology.

This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Soft computing includes several intelligent computing paradigms, like fuzzy logic, neural networks, and bio-inspired optimization algorithms. This book describes the application of soft computing techniques to intelligent control, pattern recognition, and optimization problems. The book is organized in four main parts. The first part deals with nature-inspired optimization methods and their applications. Papers included in this part propose new models for achieving intelligent optimization in different application areas. The second part discusses hybrid intelligent systems for achieving control. Papers included in this part make use of nature-inspired techniques, like evolutionary algorithms, fuzzy logic and neural networks, for the optimal design of intelligent controllers for different kind of applications. Papers in the third part focus on intelligent techniques for pattern recognition and propose new methods to solve complex pattern recognition problems. The fourth part discusses new theoretical concepts and methods for the application of soft computing to many different areas, such as natural language processing, clustering and optimization.

The two-volume set LNCS 8935 and 8936 constitutes the thoroughly refereed proceedings of the 21st International Conference on Multimedia Modeling, MMM 2015, held in Sydney, Australia, in January 2015. The 49 revised regular papers, 24 poster presentations, were carefully reviewed and selected from 189 submissions. For the three special session, a total of 18 papers were accepted for MMM 2015. The three special sessions are Personal (Big) Data Modeling for Information Access and Retrieval, Social Geo-Media Analytics and Retrieval and Image or video processing, semantic analysis and understanding. In addition, 9 demonstrations and 9 video showcase papers were accepted for MMM 2015. The accepted contributions included in these two volumes represent the state-of-the-art in multimedia modeling research and cover a diverse range of topics including: Image and Video Processing, Multimedia encoding and streaming, applications of multimedia modelling and 3D and augmented reality.

In den letzten Jahren hat sich der Workshop "Bildverarbeitung fur dieMedizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2016wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefungder Gesprache zwischen Wissenschaftlern, Industrie und Anwendern. DieBeitrage dieses Bandes - einige davon in englischer Sprache - umfassen alleBereiche der medizinischen Bildverarbeitung, insbesondere Bildgebungund -akquisition, Molekulare Bildgebung, Visualisierung und Animation, Anatomische Atlanten, Patientenindividuelle Simulation und Planung, Biomechanische Modellierung, Bildverarbeitung in der Telemedizin, Bildgestutzte Roboter, Chirurgische Simulatoren u.v.m.

This book constitutes the refereed proceedings of the European Design Science Symposium, EDSS 2013 held in Dublin, Ireland, in November 2013. The 9 papers presented together with two invited papers were carefully reviewed and selected from 18 submissions. The papers deal with various topics in the design science research.

This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field. This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.

Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.

This book constitutes thoroughly revised and selected papers from the 10th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2015, held in Berlin, Germany, in March 2015. VISIGRAPP comprises GRAPP, International Conference on Computer Graphics Theory and Applications; IVAPP, International Conference on Information Visualization Theory and Applications; and VISAPP, International Conference on Computer Vision Theory and Applications. The 23 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 529 submissions. The book also contains one invited talk in full-paper length. The regular papers were organized in topical sections named: computer graphics theory and applications; information visualization theory and applications; and computer vision theory and applications.