This monograph presents selected areas of application of pattern recognition and classification approaches including handwriting recognition, medical image analysis and interpretation, development of cognitive systems for image computer understanding, moving object detection, advanced image filtration and intelligent multi-object labelling and classification. It is directed to the scientists, application engineers, professors, professors and students will find this book useful.
The book is a collection of invited papers on Computational Intelligence for Privacy and Security. The majority of the chapters are extended versions of works presented at the special session on Computational Intelligence for Privacy and Security of the International Joint Conference on Neural Networks (IJCNN-2010) held July 2010 in Barcelona, Spain. The book is devoted to Computational Intelligence for Privacy and Security. It provides an overview of the most recent advances on the Computational Intelligence techniques being developed for Privacy and Security. The book will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of Computational Intelligence for Privacy and Security.
This volume details the latest state-of-the-art research on computational intelligence paradigms in healthcare in the intelligent agent environment. The book presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems. These include intelligent synthetic characters, man-machine interface, menu generators, analysis of user acceptance, pictures archiving and communication systems.
This book features research on the innovative applications of advanced computational intelligence paradigms. Coverage includes architectures of computational intelligence paradigms, knowledge discovery, pattern classification, and gene linkage analysis.
The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.
The textbook at hand aims to provide an introduction to the use of automated methods for gathering strategic competitive intelligence. Hereby, the text does not describe a singleton research discipline in its own right, such as machine learning or Web mining. It rather contemplates an application scenario, namely the gathering of knowledge that appears of paramount importance to organizations, e.g., companies and corporations. To this end, the book first summarizes the range of research disciplines that contribute to addressing the issue, extracting from each those grains that are of utmost relevance to the depicted application scope. Moreover, the book presents systems that put these techniques to practical use (e.g., reputation monitoring platforms) and takes an inductive approach to define the gestalt of mining for competitive strategic intelligence by selecting major use cases that are laid out and explained in detail. These pieces form the first part of the book. Each of those use cases is backed by a number of research papers, some of which are contained in its largely original version in the second part of the monograph.
Cognitive Information Systems in Management Sciences summarizes the body of work in this area, taking an analytical approach to interpreting the data, while also providing an approach that can be used for practical implementation in the fields of computing, economics, and engineering. Using numerous illustrative examples, and following both theoretical and practical results, Dr. Lidia Ogiela discusses the concepts and principles of cognitive information systems, the relationship between intelligent computer data analysis, and how to utilize computational intelligent approaches to enhance information retrieval. Real world implantation use cases round out the book, with valuable scenarios covering management science, computer science, and engineering. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS - Discusses the basic concepts and principles in cognitive information systems, providing 'real-world' implementation examples - Explains the relationship between intelligent computer data analysis and how to utilize computational intelligent approaches to enhance information retrieval - Provides a unified structured approach that can be used to develop information flow in cognitive management systems
There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction and computational intelligence, as Supervised and Unsupervised Pattern Recognition does. This volume describes the application of a novel, unsupervised pattern recognition scheme to the classification of various types of waveforms and images. This substantial collection of recent research begins with an introduction to Neural Networks, classifiers, and feature extraction methods. It then addresses unsupervised and fuzzy neural networks and their applications to handwritten character recognition and recognition of normal and abnormal visual evoked potentials. The third section deals with advanced neural network architectures-including modular design-and their applications to medicine and three-dimensional NN architecture simulating brain functions. The final section discusses general applications and simulations, such as the establishment of a brain-computer link, speaker identification, and face recognition. In the quickly changing field of computational intelligence, every discovery is significant. Supervised and Unsupervised Pattern Recognition gives you access to many notable findings in one convenient volume.
This book is a selection of results obtained within one year of research performed under SYNAT - a nation-wide scientific project aiming to create an infrastructure for scientific content storage and sharing for academia, education and open knowledge society in Poland. The selection refers to the research in artificial intelligence, knowledge discovery and data mining, information retrieval and natural language processing, addressing the problems of implementing intelligent tools for building a scientific information platform. The idea of this book is based on the very successful SYNAT Project Conference and the SYNAT Workshop accompanying the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011). The papers included in this book present an overview and insight into such topics as architecture of scientific information platforms, semantic clustering, ontology-based systems, as well as, multimedia data processing.
Service orientation is emerging nowadays at multiple organizational levels in enterprise business, and it leverages technology in response to the growing need for greater business integration, flexibility and agility of manufacturing enterprises. The Service Oriented Architecture (SOA) analysed throughout the book represents a technical architecture, a business modelling concept, a type of infrastructure, an integration source and a new way of viewing units of automation within the enterprise. The primary goal of SOA is to align the business world with the world of information technology in a way that makes both more effective. The service value creation model at enterprise level consists of using a Service Component Architecture for business process applications, based on entities which handle services. In this view a service is a piece of software encapsulating the business/control logic or resource functionality of an enterprise entity that exhibits an individual competence and responds to a specific request to fulfil a local (operation) or global objective (batch production). The value creation model is based on a 2-stage approach: • Agentification: complex manufacturing processes are split in services provided by informational agents which are discovered, accessed and executed. This leads to a modular, reusable, agile and easy integrate integration. • Holonification: holons link the material flow and physical entities of the manufacturing processes with the informational part (IT services realized by distributed intelligence) facilitating thus traceability the developing of flexible control systems. This book gathers contributions from scientists, researchers and industrialists on concepts, methods, frameworks and implementing issues addressing trends in the service orientation of control technology and management applied to manufacturing enterprise. This book gathers contributions from scientists, researchers and industrialists on concepts, methods, frameworks and implementing issues addressing trends in the service orientation of control technology and management applied to manufacturing enterprise.
