Author: Tao Jiang
Publisher: Springer Science & Business Media
ISBN: 9783540633570
Category : Computers
Languages : en
Pages : 540
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Book Description
The book is aimed at graduate students, researchers, engineers and physicists involved in fluid computations. An up-to-date account is given of the present state of the art of numerical methods employed in computational fluid dynamics. The underlying numerical principles are treated with a fair amount of detail, using elementary methods. Attention is given to the difficulties arising from geometric complexity of the flow domain. Uniform accuracy for singular perturbation problems is studied, pointing the way to accurate computation of flows at high Reynolds number. Unified methods for compressible and incompressible flows are discussed. A treatment of the shallow-water equations is included. A basic introduction is given to efficient iterative solution methods. Many pointers are given to the current literature, facilitating further study.
Author: Rainer Bodendiek
Publisher: Springer Science & Business Media
ISBN: 3642469086
Category : Mathematics
Languages : en
Pages : 769
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Book Description
Graph Theory is a part of discrete mathematics characterized by the fact of an extremely rapid development during the last 10 years. The number of graph theoretical paper as well as the number of graph theorists increase very strongly. The main purpose of this book is to show the reader the variety of graph theoretical methods and the relation to combinatorics and to give him a survey on a lot of new results, special methods, and interesting informations. This book, which grew out of contributions given by about 130 authors in honour to the 70th birthday of Gerhard Ringel, one of the pioneers in graph theory, is meant to serve as a source of open problems, reference and guide to the extensive literature and as stimulant to further research on graph theory and combinatorics.
Author:
Publisher: SIAM
ISBN: 9780898713497
Category : Computers
Languages : en
Pages : 668
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Book Description
The proceedings of the January 1995 symposium, sponsored by the ACM Special Interest Group on Algorithms and Computation Theory and the SIAM Activity Group on Discrete Mathematics, comprise 70 papers. Among the topics: on-line approximate list indexing with applications; finding subsets maximizing minimum structures; register allocation in structured programs; and splay trees for data compression. No index. Annotation copyright by Book News, Inc., Portland, OR
Author: Carsten Steger
Publisher: John Wiley & Sons
ISBN: 3527413650
Category : Science
Languages : en
Pages : 533
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Book Description
The second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.
Author: P.J. Fleming
Publisher: Elsevier
ISBN: 1483297934
Category : Technology & Engineering
Languages : en
Pages : 374
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Book Description
This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.
Author: Mani Khanuja
Publisher: Packt Publishing Ltd
ISBN: 1803244445
Category : Computers
Languages : en
Pages : 382
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Book Description
Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.
Author: Khaled Elbassioni
Publisher: Springer
ISBN: 3662489716
Category : Computers
Languages : en
Pages : 786
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Book Description
This book constitutes the refereed proceedings of the 26th International Symposium on Algorithms and Computation, ISAAC 2015, held in Nagoya, Japan, in December 2015. The 65 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 180 submissions for inclusion in the book. The focus of the volume is on the following topics: computational geometry; data structures; combinatorial optimization and approximation algorithms; randomized algorithms; graph algorithms and FPT; computational complexity; graph drawing and planar graphs; online and streaming algorithms; and string and DNA algorithms.
Author: Mike Paterson
Publisher: Springer
ISBN: 3540452532
Category : Computers
Languages : en
Pages : 463
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Book Description
This book constitutes the refereed proceedings of the 8th Annual European Symposium on Algorithms, ESA 2000, held in Saarbrücken, Germany in September 2000. The 39 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the book. Among the topics addressed are parallelism, distributed systems, approximation, combinatorial optimization, computational biology, computational geometry, external-memory algorithms, graph algorithms, network algorithms, online algorithms, data compression, symbolic computation, pattern matching, and randomized algorithms.
Author: M. Bennamoun
Publisher: Springer Science & Business Media
ISBN: 1447137221
Category : Computers
Languages : en
Pages : 352
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Book Description
Automatie object recognition is a multidisciplinary research area using con cepts and tools from mathematics, computing, optics, psychology, pattern recognition, artificial intelligence and various other disciplines. The purpose of this research is to provide a set of coherent paradigms and algorithms for the purpose of designing systems that will ultimately emulate the functions performed by the Human Visual System (HVS). Hence, such systems should have the ability to recognise objects in two or three dimensions independently of their positions, orientations or scales in the image. The HVS is employed for tens of thousands of recognition events each day, ranging from navigation (through the recognition of landmarks or signs), right through to communication (through the recognition of characters or people themselves). Hence, the motivations behind the construction of recognition systems, which have the ability to function in the real world, is unquestionable and would serve industrial (e.g. quality control), military (e.g. automatie target recognition) and community needs (e.g. aiding the visually impaired). Scope, Content and Organisation of this Book This book provides a comprehensive, yet readable foundation to the field of object recognition from which research may be initiated or guided. It repre sents the culmination of research topics that I have either covered personally or in conjunction with my PhD students. These areas include image acqui sition, 3-D object reconstruction, object modelling, and the matching of ob jects, all of which are essential in the construction of an object recognition system.
Author: Maria M. P. Petrou
Publisher: John Wiley & Sons
ISBN: 047074586X
Category : Science
Languages : en
Pages : 835
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Book Description
Following the success of the first edition, this thoroughly updated second edition of Image Processing: The Fundamentals will ensure that it remains the ideal text for anyone seeking an introduction to the essential concepts of image processing. New material includes image processing and colour, sine and cosine transforms, Independent Component Analysis (ICA), phase congruency and the monogenic signal and several other new topics. These updates are combined with coverage of classic topics in image processing, such as orthogonal transforms and image enhancement, making this a truly comprehensive text on the subject. Key features: Presents material at two levels of difficulty: the main text addresses the fundamental concepts and presents a broad view of image processing, whilst more advanced material is interleaved in boxes throughout the text, providing further reference for those who wish to examine each technique in depth. Contains a large number of fully worked out examples. Focuses on an understanding of how image processing methods work in practice. Illustrates complex algorithms on a step-by-step basis, and lists not only the good practices but also identifies the pitfalls in each case. Uses a clear question and answer structure. Includes a CD containing the MATLAB® code of the various examples and algorithms presented in the book. There is also an accompanying website with slides available for download for instructors as a teaching resource. Image Processing: The Fundamentals, Second Edition is an ideal teaching resource for both undergraduate and postgraduate students. It will also be of value to researchers of various disciplines from medicine to mathematics with a professional interest in image processing
