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Type 2 Fuzzy Graphical Models For Pattern Recognition
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Book Synopsis Type-2 Fuzzy Graphical Models for Pattern Recognition by : Jia Zeng
Download or read book Type-2 Fuzzy Graphical Models for Pattern Recognition written by Jia Zeng and published by Springer. This book was released on 2014-09-17 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.
Book Synopsis Artificial Intelligence and Evolutionary Computations in Engineering Systems by : Subhransu Sekhar Dash
Download or read book Artificial Intelligence and Evolutionary Computations in Engineering Systems written by Subhransu Sekhar Dash and published by Springer. This book was released on 2017-07-11 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to deliberate and state their research findings, discuss the latest advancements and explore the future directions in the emerging areas of engineering and technology. The book presents original work and novel ideas, information, techniques and applications in the field of communication, computing and power technologies.
Book Synopsis Clustering Techniques for Image Segmentation by : Fasahat Ullah Siddiqui
Download or read book Clustering Techniques for Image Segmentation written by Fasahat Ullah Siddiqui and published by Springer Nature. This book was released on 2021-10-29 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the workings of major clustering techniques along with their advantages and shortcomings. After introducing the topic, the authors illustrate their modified version that avoids those shortcomings. The book then introduces four modified clustering techniques, namely the Optimized K-Means (OKM), Enhanced Moving K-Means-1(EMKM-1), Enhanced Moving K-Means-2(EMKM-2), and Outlier Rejection Fuzzy C-Means (ORFCM). The authors show how the OKM technique can differentiate the empty and zero variance cluster, and the data assignment procedure of the K-mean clustering technique is redesigned. They then show how the EMKM-1 and EMKM-2 techniques reform the data-transferring concept of the Adaptive Moving K-Means (AMKM) to avoid the centroid trapping problem. And that the ORFCM technique uses the adaptable membership function to moderate the outlier effects on the Fuzzy C-meaning clustering technique. This book also covers the working steps and codings of quantitative analysis methods. The results highlight that the modified clustering techniques generate more homogenous regions in an image with better shape and sharp edge preservation. Showcases major clustering techniques, detailing their advantages and shortcomings; Includes several methods for evaluating the performance of segmentation techniques; Presents several applications including medical diagnosis systems, satellite imaging systems, and biometric systems.
Book Synopsis Advances in Signal Processing and Intelligent Recognition Systems by : Sabu M. Thampi
Download or read book Advances in Signal Processing and Intelligent Recognition Systems written by Sabu M. Thampi and published by Springer. This book was released on 2015-12-24 with total page 711 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.
Book Synopsis Analysis of Images, Social Networks and Texts by : Mikhail Yu. Khachay
Download or read book Analysis of Images, Social Networks and Texts written by Mikhail Yu. Khachay and published by Springer. This book was released on 2015-12-04 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Fourth International Conference on Analysis of Images, Social Networks and Texts, AIST 2015, held in Yekaterinburg, Russia, in April 2015. The 24 full and 8 short papers were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on analysis of images and videos; pattern recognition and machine learning; social network analysis; text mining and natural language processing.
Book Synopsis Soft Computing for Recognition based on Biometrics by : Patricia Melin
Download or read book Soft Computing for Recognition based on Biometrics written by Patricia Melin and published by Springer. This book was released on 2010-09-30 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: We describe in this book, bio-inspired models and applications of hybrid intel- gent systems using soft computing techniques for image analysis and pattern r- ognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of classification methods and applications, which are basically papers that propose new models for classification to solve general pr- lems and applications. The second part contains papers with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques, like modular neural networks, for achieving pattern r- ognition based on biometric measures. The third part contains papers with the theme of bio-inspired optimization methods and applications to diverse problems. The fourth part contains papers that deal with general theory and algorithms of bio-inspired methods, like neural networks and evolutionary algorithms. The fifth part contains papers on computer vision applications of soft computing methods. In the part of classification methods and applications there are 5 papers that - scribe different contributions on fuzzy logic and bio-inspired models with appli- tion in classification for medical images and other data.
Book Synopsis Advances in Artificial Intelligence by : Jose A. Lozano
Download or read book Advances in Artificial Intelligence written by Jose A. Lozano and published by Springer Science & Business Media. This book was released on 2011-10-28 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2009, held in La Laguna, Canary Islands, Spain, in November 2011. The 50 revised full papers presented were carefully selected from 149 submissions. The papers are organized in topical sections on agent-based and multi-agent systems; machine learning; knowledge representation, logic, search and planning; multidisciplinary topics and applications; vision and robotics; soft computing; Web intelligence and information retrieval.
Book Synopsis Dermoscopy Image Analysis by : M. Emre Celebi
Download or read book Dermoscopy Image Analysis written by M. Emre Celebi and published by CRC Press. This book was released on 2015-10-16 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifyin
Book Synopsis Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition by : Patricia Melin
Download or read book Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition written by Patricia Melin and published by Springer Science & Business Media. This book was released on 2011-10-18 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Book Synopsis Type-2 Fuzzy Graphical Models for Pattern Recognition by : Jia Zeng
Download or read book Type-2 Fuzzy Graphical Models for Pattern Recognition written by Jia Zeng and published by . This book was released on 2014-10-31 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis New Trends in Computational Vision and Bio-inspired Computing by : S. Smys
Download or read book New Trends in Computational Vision and Bio-inspired Computing written by S. Smys and published by Springer Nature. This book was released on 2020-09-27 with total page 1664 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume 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. In this book, researchers, graduate students and professionals will find innovative solutions to real-world problems in industry and society as a whole, together with inspirations for further research.
Book Synopsis Pattern Recognition with Fuzzy Objective Function Algorithms by : James C. Bezdek
Download or read book Pattern Recognition with Fuzzy Objective Function Algorithms written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.
Book Synopsis Handbook of Pattern Recognition and Computer Vision by : Chi-hau Chen
Download or read book Handbook of Pattern Recognition and Computer Vision written by Chi-hau Chen and published by World Scientific. This book was released on 2010 with total page 797 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both pattern recognition and computer vision have experienced rapid progress in the last twenty-five years. This book provides the latest advances on pattern recognition and computer vision along with their many applications. It features articles written by renowned leaders in the field while topics are presented in readable form to a wide range of readers. The book is divided into five parts: basic methods in pattern recognition, basic methods in computer vision and image processing, recognition applications, life science and human identification, and systems and technology. There are eight new chapters on the latest developments in life sciences using pattern recognition as well as two new chapters on pattern recognition in remote sensing.
Book Synopsis Global Trends in Intelligent Computing Research and Development by : Tripathy, B.K.
Download or read book Global Trends in Intelligent Computing Research and Development written by Tripathy, B.K. and published by IGI Global. This book was released on 2013-12-31 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the amount of accumulated data across a variety of fields becomes harder to maintain, it is essential for a new generation of computational theories and tools to assist humans in extracting knowledge from this rapidly growing digital data. Global Trends in Intelligent Computing Research and Development brings together recent advances and in depth knowledge in the fields of knowledge representation and computational intelligence. Highlighting the theoretical advances and their applications to real life problems, this book is an essential tool for researchers, lecturers, professors, students, and developers who have seek insight into knowledge representation and real life applications.
Book Synopsis Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications by : Oscar Castillo
Download or read book Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications written by Oscar Castillo and published by Springer Nature. This book was released on 2020-02-27 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the latest advances in fuzzy logic, neural networks, and optimization algorithms, as well as their hybrid intelligent combinations, and their applications in the areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The topic is highly relevant as most current intelligent systems and devices use some form of intelligent feature to enhance their performance. The book also presents new and advanced models and algorithms of type-2 fuzzy logic and intuitionistic fuzzy systems, which are of great interest to researchers in these areas. Further, it proposes novel, nature-inspired optimization algorithms and innovative neural models. Featuring contributions on theoretical aspects as well as applications, the book appeals to a wide audience.
Book Synopsis Uncertain Spatiotemporal Data Management for the Semantic Web by : Bai, Luyi
Download or read book Uncertain Spatiotemporal Data Management for the Semantic Web written by Bai, Luyi and published by IGI Global. This book was released on 2024-03-01 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the world of data management, one of the most formidable challenges faced by academic scholars is the effective handling of spatiotemporal data within the semantic web. As our world continues to change dynamically with time, nearly every aspect of our lives, from environmental monitoring to urban planning and beyond, is intrinsically linked to time and space. This synergy has given rise to an avalanche of spatiotemporal data, and the pressing question is how to manage, model, and query this voluminous information effectively. The existing approaches often fall short in addressing the intricacies and uncertainties that come with spatiotemporal data, leaving scholars struggling to unlock its full potential. Uncertain Spatiotemporal Data Management for the Semantic Web is the definitive solution to the challenges faced by academic scholars in the realm of spatiotemporal data. This book offers a visionary approach to an all-encompassing guide in modeling and querying spatiotemporal data using innovative technologies like XML and RDF. Through a meticulously crafted set of chapters, this book sheds light on the nuances of spatiotemporal data and also provides practical solutions that empower scholars to navigate the complexities of this domain effectively.
