Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems written by Eyke Hüllermeier and published by Springer Science & Business Media. This book was released on 2010-06-17 with total page 783 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, held in Dortmund, Germany, in June 2010.
Download or read book An Improved Method for Image Segmentation Using K Means Clustering with Neutrosophic Logic written by Mohammad Naved Qureshi and published by Infinite Study. This book was released on with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: Images are one of the primary media for sharing information. The image segmentation is an important image processing approach, which analyzes what is inside the image. Image segmentation can be used in content-based image retrieval, image feature extraction, pattern recognition, etc. In this work, clustering based image segmentation method used and modified by introducing neutrosophic logic.
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.
Download or read book Metaheuristics for Data Clustering and Image Segmentation written by Meera Ramadas and published by Springer. This book was released on 2018-12-12 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
Download or read book Advancements in Computer Vision and Image Processing written by Garcia-Rodriguez, Jose and published by IGI Global. This book was released on 2018-04-06 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in computer vision and image processing has grown in recent years with the advancement of everyday technologies such as smartphones, computer games, and social robotics. These advancements have allowed for advanced algorithms that have improved the processing capabilities of these technologies. Advancements in Computer Vision and Image Processing is a critical scholarly resource that explores the impact of new technologies on computer vision and image processing methods in everyday life. Featuring coverage on a wide range of topics including 3D visual localization, cellular automata-based structures, and eye and face recognition, this book is geared toward academicians, technology professionals, engineers, students, and researchers seeking current research on the development of sophisticated algorithms to process images and videos in real time.
Download or read book Data Clustering and Image Segmentation Through Genetic Algorithms written by Sujata Dash and published by Engineering Science Reference. This book was released on 2018-08-03 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides a broad overview of genetic algorithms, clustering algorithms influenced by genetic algorithms, improvements attained in the field of image segmentation and their application by using genetic algorithms. It also explores the comparative analysis of earlier methods and the recent ones proposed with the use of genetic algorithms"--
Download or read book Clustering and Image Segmentation written by Hedayetul Islam Shovon and published by LAP Lambert Academic Publishing. This book was released on 2012-02 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clustering can be considered the most important unsupervised learning problem. In briefly, the process of organizing objects into groups whose members are similar in some way. This book presents an overview of existing clustering algorithms with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners.Determining the number of cluster is a running burning question for clustering. I tried to propose a method for clustering validation. I present taxonomy of clustering techniques, and identify crosscutting themes and recent advances. I also describe a big famous field of application of clustering- Image segmentation.
Download or read book Image Segmentation by Clustering written by Guy Barrett Coleman and published by . This book was released on 1977 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation describes a procedure for segmenting imagery using digital techniques and is based on the mathematical model. The classifer does not require training prototypes, that is, it operates in an unsupervised mode. The procedure is general in that the features most useful for the particular image to be segmented are selected by the algorithm. The algorithm operates without any human interaction. The features used are based on brightness and texture in regions centered on every picture element in the image. To perform an elementary pre-classification of local regions, a filter based on the mode of the local area histogram is proposed and used in segmenting images. The basic procedure is a K-means clustering algorithm which converges to a local minimum in the average squared inter-cluster distance for a specified number of clusters. The algorithm iterates on the number of clusters, evaluating the clustering based on a parameter of clustering quality. The parameter proposed is a product of between and within cluster scatter measures, which achieves a maximum value that is postulated to represent an intrinsic number of clusters in the data.
Download or read book Metaheuristic Algorithms for Image Segmentation Theory and Applications written by Diego Oliva and published by Springer. This book was released on 2019-03-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implemented using various metaheuristics and hybridization techniques leading to a broader understanding of how image segmentation problems can be solved from an optimization perspective. The field of image processing is constantly changing due to the extensive integration of cameras in devices; for example, smart phones and cars now have embedded cameras. The images have to be accurately analyzed, and crucial pre-processing steps, like image segmentation, and artificial intelligence, including metaheuristics, are applied in the automatic analysis of digital images. Metaheuristic algorithms have also been used in various fields of science and technology as the demand for new methods designed to solve complex optimization problems increases. This didactic book is primarily intended for undergraduate and postgraduate students of science, engineering, and computational mathematics. It is also suitable for courses such as artificial intelligence, advanced image processing, and computational intelligence. The material is also useful for researches in the fields of evolutionary computation, artificial intelligence, and image processing.
Download or read book Cognitive Informatics and Soft Computing written by Pradeep Kumar Mallick and published by Springer. This book was released on 2018-08-11 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents new approaches and methods for solving real-world problems. It offers, in particular, exploratory research that describes novel approaches in the fields of Cognitive Informatics, Cognitive Computing, Computational Intelligence, Advanced Computing, Hybrid Intelligent Models and Applications. New algorithms and methods in a variety of fields are also presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of Computer Science, Artificial Intelligence, Cybernetics, Automation Control Theory and Software Engineering.
Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.
Download or read book Self Organizing Migrating Algorithm written by Donald Davendra and published by Springer. This book was released on 2016-02-04 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
Download or read book Robust Clustering and Image Segmentation written by Klaus Köster and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Laws of Seeing written by Wolfgang Metzger and published by MIT Press. This book was released on 2009-08-21 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first English translation of a classic work in vision science from 1936 by a leading figure in the Gestalt movement, covering topics that continue to be major issues in vision research today. This classic work in vision science, written by a leading figure in Germany's Gestalt movement in psychology and first published in 1936, addresses topics that remain of major interest to vision researchers today. Wolfgang Metzger's main argument, drawn from Gestalt theory, is that the objects we perceive in visual experience are not the objects themselves but perceptual effigies of those objects constructed by our brain according to natural rules. Gestalt concepts are currently being increasingly integrated into mainstream neuroscience by researchers proposing network processing beyond the classical receptive field. Metzger's discussion of such topics as ambiguous figures, hidden forms, camouflage, shadows and depth, and three-dimensional representations in paintings will interest anyone working in the field of vision and perception, including psychologists, biologists, neurophysiologists, and researchers in computational vision—and artists, designers, and philosophers. Each chapter is accompanied by compelling visual demonstrations of the phenomena described; the book includes 194 illustrations, drawn from visual science, art, and everyday experience, that invite readers to verify Metzger's observations for themselves. Today's researchers may find themselves pondering the intriguing question of what effect Metzger's theories might have had on vision research if Laws of Seeing and its treasure trove of perceptual observations had been available to the English-speaking world at the time of its writing.
Download or read book Image Segmentation written by Tao Lei and published by John Wiley & Sons. This book was released on 2022-10-11 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Segmentation Summarizes and improves new theory, methods, and applications of current image segmentation approaches, written by leaders in the field The process of image segmentation divides an image into different regions based on the characteristics of pixels, resulting in a simplified image that can be more efficiently analyzed. Image segmentation has wide applications in numerous fields ranging from industry detection and bio-medicine to intelligent transportation and architecture. Image Segmentation: Principles, Techniques, and Applications is an up-to-date collection of recent techniques and methods devoted to the field of computer vision. Covering fundamental concepts, new theories and approaches, and a variety of practical applications including medical imaging, remote sensing, fuzzy clustering, and watershed transform. In-depth chapters present innovative methods developed by the authors—such as convolutional neural networks, graph convolutional networks, deformable convolution, and model compression—to assist graduate students and researchers apply and improve image segmentation in their work. Describes basic principles of image segmentation and related mathematical methods such as clustering, neural networks, and mathematical morphology. Introduces new methods for achieving rapid and accurate image segmentation based on classic image processing and machine learning theory. Presents techniques for improved convolutional neural networks for scene segmentation, object recognition, and change detection, etc. Highlights the effect of image segmentation in various application scenarios such as traffic image analysis, medical image analysis, remote sensing applications, and material analysis, etc. Image Segmentation: Principles, Techniques, and Applications is an essential resource for undergraduate and graduate courses such as image and video processing, computer vision, and digital signal processing, as well as researchers working in computer vision and image analysis looking to improve their techniques and methods.
Download or read book Fuzzy Systems in Bioinformatics and Computational Biology written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2009-04-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties. Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and analysis approaches are also becoming popular in analyzing biological data and modeling biological systems. Numerous research and application results have been reported that demonstrated the effectiveness of fuzzy logic in solving a wide range of biological problems found in bioinformatics, biomedical engineering, and computational biology. Contributed by leading experts world-wide, this edited book contains 16 chapters presenting representative research results on the application of fuzzy systems to genome sequence assembly, gene expression analysis, promoter analysis, cis-regulation logic analysis and synthesis, reconstruction of genetic and cellular networks, as well as biomedical problems, such as medical image processing, electrocardiogram data classification and anesthesia monitoring and control. This volume is a valuable reference for researchers, practitioners, as well as graduate students working in the field of bioinformatics, biomedical engineering and computational biology.
Download or read book Improving Clustering based Image Segmentation Through Learning written by Hui Zhang and published by . This book was released on 2007 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
