Development of Hypergraph Based Techniques for Selected Image Engineering Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Development of Hypergraph Based Techniques for Selected Image Engineering Applications PDF full book. Access full book title Development of Hypergraph Based Techniques for Selected Image Engineering Applications by Dr B Rajesh Kanna. Download full books in PDF and EPUB format.
Author: Dr B Rajesh Kanna
Publisher: Archers & Elevators Publishing House
ISBN: 9386501635
Category : Antiques & Collectibles
Languages : en
Pages :
Get Book Here
Book Description
Author: Dr B Rajesh Kanna
Publisher: Archers & Elevators Publishing House
ISBN: 9386501635
Category : Antiques & Collectibles
Languages : en
Pages :
Get Book Here
Book Description
Author: Pai Zheng
Publisher: Elsevier
ISBN: 0323852483
Category : Technology & Engineering
Languages : en
Pages : 254
Get Book Here
Book Description
Smart Product-Service Systems draws on innovative practice and academic research to demonstrate the unique benefits of Smart PSS and help facilitate its effective implementation. This comprehensive guide explains how Smart PSS reshapes product-service design in several unique aspects, including a closed-loop product design and redesign manner, value co-creation with integrated human-machine intelligence, and solution design context-awareness. Readers in industry as well as academia will find this to be an invaluable guide to the current body of technical knowledge on Smart Product-Service Systems (Smart PSS), future research trajectories, and experiences of implementation. Rapid development of information and communication technologies, artificial intelligence, and digital technologies have driven today’s industries towards the so-called digital servitization era. As a result, a promising IT-driven business paradigm, known as Smart Product-Service Systems (Smart PSS) has emerged, where a large amount of low cost, high performance smart, connected products are leveraged, together with their generated on-demand services, as a single solution bundle to meet individual customer needs. Explains what factors a company needs to consider in their transition towards digital servitization and its advantages Describes how this field relates to the sustainability movement, and how Smart PSS can be implemented in a sustainable way Includes detailed case studies from different industries, including DELTA Electronics Inc. Singapore (smart commercialization), COMAC aviation industry (smart manufacturing servitization), and Van High Tech (smart building services)
Author: Aidan Hogan
Publisher: Morgan & Claypool Publishers
ISBN: 1636392369
Category : Computers
Languages : en
Pages : 257
Get Book Here
Book Description
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Author: Alain Bretto
Publisher: Springer Science & Business Media
ISBN: 3319000802
Category : Mathematics
Languages : en
Pages : 129
Get Book Here
Book Description
This book provides an introduction to hypergraphs, its aim being to overcome the lack of recent manuscripts on this theory. In the literature hypergraphs have many other names such as set systems and families of sets. This work presents the theory of hypergraphs in its most original aspects, while also introducing and assessing the latest concepts on hypergraphs. The variety of topics, their originality and novelty are intended to help readers better understand the hypergraphs in all their diversity in order to perceive their value and power as mathematical tools. This book will be a great asset to upper-level undergraduate and graduate students in computer science and mathematics. It has been the subject of an annual Master's course for many years, making it also ideally suited to Master's students in computer science, mathematics, bioinformatics, engineering, chemistry, and many other fields. It will also benefit scientists, engineers and anyone else who wants to understand hypergraphs theory.
Author: Francesco Ricci
Publisher: Springer
ISBN: 148997637X
Category : Computers
Languages : en
Pages : 1008
Get Book Here
Book Description
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
Author: Stephane Mallat
Publisher: Elsevier
ISBN: 0080520839
Category : Computers
Languages : en
Pages : 663
Get Book Here
Book Description
This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École Polytechnique in Paris. Provides a broad perspective on the principles and applications of transient signal processing with wavelets Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet Content is accessible on several level of complexity, depending on the individual reader's needs New to the Second Edition Optical flow calculation and video compression algorithms Image models with bounded variation functions Bayes and Minimax theories for signal estimation 200 pages rewritten and most illustrations redrawn More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics
Author: Guojun Gan
Publisher: SIAM
ISBN: 1611976332
Category : Mathematics
Languages : en
Pages : 430
Get Book Here
Book Description
Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Author: John L. Pfaltz
Publisher: Springer Science & Business Media
ISBN: 3540221204
Category : Mathematics
Languages : en
Pages : 515
Get Book Here
Book Description
This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Applications of Graph Transformations with Industrial Relevance, AGTIVE 2003, held in Charlotesville, Virginia, USA in September/October 2003. The 27 revised full papers and 11 revised demo papers presented together with 2 invited papers and 5 workshop reports were carefully selected during iterated rounds of reviewing and revision. The papers are organized in topical sections on Web applications; data structures and data bases; engineering applications; agent-oriented and functional programs and distribution; object- and aspect-oriented systems; natural languages: processing and structuring; reengineering; reuse and integration; modeling languages; bioinformatics; and multimedia, picture, and visual languages.
Author: Zhiyuan Zhiyuan Liu
Publisher: Springer Nature
ISBN: 3031015878
Category : Computers
Languages : en
Pages : 109
Get Book Here
Book Description
Graphs are useful data structures in complex real-life applications such as modeling physical systems, learning molecular fingerprints, controlling traffic networks, and recommending friends in social networks. However, these tasks require dealing with non-Euclidean graph data that contains rich relational information between elements and cannot be well handled by traditional deep learning models (e.g., convolutional neural networks (CNNs) or recurrent neural networks (RNNs)). Nodes in graphs usually contain useful feature information that cannot be well addressed in most unsupervised representation learning methods (e.g., network embedding methods). Graph neural networks (GNNs) are proposed to combine the feature information and the graph structure to learn better representations on graphs via feature propagation and aggregation. Due to its convincing performance and high interpretability, GNN has recently become a widely applied graph analysis tool. This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.
Author: Lasse Kliemann
Publisher: Springer
ISBN: 3319494872
Category : Computers
Languages : en
Pages : 428
Get Book Here
Book Description
Algorithm Engineering is a methodology for algorithmic research that combines theory with implementation and experimentation in order to obtain better algorithms with high practical impact. Traditionally, the study of algorithms was dominated by mathematical (worst-case) analysis. In Algorithm Engineering, algorithms are also implemented and experiments conducted in a systematic way, sometimes resembling the experimentation processes known from fields such as biology, chemistry, or physics. This helps in counteracting an otherwise growing gap between theory and practice.
