image data structures and converting algorithms

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Simon Harris Beginning Algorithms Simon Harris Beginning Algorithms
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Simon Harris Beginning Algorithms


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3110.99 руб.

Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursion Elementary data structures such as lists, stacks, and queues Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort Advanced data structures such as binary trees, ternary trees, and heaps Algorithms for string searching, string matching, hashing, and computational geometry How to use test-driven development techniques to ensure your code works as intended How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.

Simon Harris Beginning Algorithms Simon Harris Beginning Algorithms
:

Simon Harris Beginning Algorithms


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3110.99 руб.

Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursion Elementary data structures such as lists, stacks, and queues Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort Advanced data structures such as binary trees, ternary trees, and heaps Algorithms for string searching, string matching, hashing, and computational geometry How to use test-driven development techniques to ensure your code works as intended How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.

Rod Stephens Essential Algorithms. A Practical Approach to Computer Algorithms Rod Stephens Essential Algorithms. A Practical Approach to Computer Algorithms
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Rod Stephens Essential Algorithms. A Practical Approach to Computer Algorithms


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4499.3 руб.

A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures such as arrays, linked lists, trees, and networks Addresses advanced data structures such as heaps, 2-3 trees, B-trees Addresses general problem-solving techniques such as branch and bound, divide and conquer, recursion, backtracking, heuristics, and more Reviews sorting and searching, network algorithms, and numerical algorithms Includes general problem-solving techniques such as brute force and exhaustive search, divide and conquer, backtracking, recursion, branch and bound, and more In addition, Essential Algorithms features a companion website that includes full instructor materials to support training or higher ed adoptions.

Pawel Cichosz Data Mining Algorithms. Explained Using R Pawel Cichosz Data Mining Algorithms. Explained Using R
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Pawel Cichosz Data Mining Algorithms. Explained Using R


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5999.06 руб.

Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

Xianchuan Yu Blind Source Separation. Theory and Applications Xianchuan Yu Blind Source Separation. Theory and Applications
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Xianchuan Yu Blind Source Separation. Theory and Applications


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14022.96 руб.

A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field. A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition Written by an expert team with accredited innovations in blind source separation and its applications in natural science Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.

J. Parker R. Algorithms for Image Processing and Computer Vision J. Parker R. Algorithms for Image Processing and Computer Vision
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J. Parker R. Algorithms for Image Processing and Computer Vision


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7390.15 руб.

A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.

Jie Liang Models and Algorithms for Biomolecules and Molecular Networks Jie Liang Models and Algorithms for Biomolecules and Molecular Networks
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Jie Liang Models and Algorithms for Biomolecules and Molecular Networks


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8623.66 руб.

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms Sampling techniques for estimating evolutionary rates and generating molecular structures Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations End-of-chapter exercises

Florence Tupin Remote Sensing Imagery Florence Tupin Remote Sensing Imagery
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Florence Tupin Remote Sensing Imagery


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12373.78 руб.

Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.

Haibo He Imbalanced Learning. Foundations, Algorithms, and Applications Haibo He Imbalanced Learning. Foundations, Algorithms, and Applications
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Haibo He Imbalanced Learning. Foundations, Algorithms, and Applications


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9599.07 руб.

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications. Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.

Carpenter James Multiple Imputation and its Application Carpenter James Multiple Imputation and its Application
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Carpenter James Multiple Imputation and its Application


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6301.08 руб.

A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.

Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications
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Xiwen Wang Relative Fidelity Processing of Seismic Data. Methods and Applications


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14997.66 руб.

This book presents a comprehensive overview of relative fidelity preservation processing methods and their applications within the oil and gas sector. Four key principles for wide-frequency relative fidelity preservation processing are illustrated throughout the text. Seismic broadband acquisition is the basis for relative fidelity preservation processing and the influence of seismic acquisition on data processing is also analyzed. The methods and principles of Kirchhoff integral migration, one-way wave equation migration and reverse time migration are also introduced and illustrated clearly. Current research of relative amplitude preservation migration algorithms is introduced, and the corresponding numerical results are also shown. RTM (reverse time migration) imaging methods based on GPU/CPU systems for complicated structures are represented. This includes GPU/CPU high performance calculations and its application to seismic exploration, two-way wave extrapolation operator and boundary conditions, imaging conditions and low frequency noise attenuation, and GPU/CPU system based RTM imaging algorithms. Migration velocity model building methods in depth domain for complicated structures are illustrated in this book. The research status and development of velocity model building are introduced. And the impacting factors are also discussed. Several different velocity model building methods are also represented and analyzed. The book also provides the reader with several case studies of field seismic data imaging in different kinds of basins to show the methods used in practice.

Kevin Murphy D. Modeling and Estimation of Structural Damage Kevin Murphy D. Modeling and Estimation of Structural Damage
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Kevin Murphy D. Modeling and Estimation of Structural Damage


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9015.67 руб.

Modelling and Estimation of Damage in Structures is a comprehensiveguide to solving the type of modelling and estimation problems associated with the physics of structural damage. Provides a model-based approach to damage identification Presents an in-depth treatment of probability theory and random processes Covers both theory and algorithms for implementing maximum likelihood and Bayesian estimation approaches Includes experimental examples of all detection and identification approaches Provides a clear means by which acquired data can be used to make decisions regarding maintenance and usage of a structure

Kostadinov Todor Pavlov Bistatic SAR / ISAR / FSR. Theory Algorithms and Program Implementation Kostadinov Todor Pavlov Bistatic SAR / ISAR / FSR. Theory Algorithms and Program Implementation
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Kostadinov Todor Pavlov Bistatic SAR / ISAR / FSR. Theory Algorithms and Program Implementation


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7853.01 руб.

Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques, and numerical experiments that confirm theoretical models are carried out. The authors suggest the program implementation of developed algorithms. A theoretical summary of the latest results in the field of bistatic radars is provided, before applying an analytical geometrical description of scenarios of bistatic synthetic aperture, inverse synthetic aperture and forward scattering radars with cooperative and non-cooperative transmitters. Signal models with linear frequency and phase code modulation are developed, and special phase modulations with C/A (coarse acquisition) and P (precision) of GPS satellite transmitters are considered. The authors suggest Matlab implementations of all geometrical models and signal formation and processing algorithms. Contents 1. Bistatic Synthetic Aperture Radar (BSAR) Survey. 2. BSAR Geometry. 3. BSAR Waveforms and Signal Models. 4. BSAR Image Reconstruction Algorithms. 5. Analytical Geometrical Determination of BSAR Resolution. 6. BSAR Experimental Results. 7. BSAR Matlab Implementation. A general theoretical description of bistatic technology within the scope of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation and processing theory. Signal formation and image reconstruction algorithms are developed in this title, with application of high informative linear frequency and phase code modulating techniques. Numerical experiments that confirm theoretical models are carried out and the authors suggest program implementation for the algorithms developed.

Mark Haidekker Advanced Biomedical Image Analysis Mark Haidekker Advanced Biomedical Image Analysis
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Mark Haidekker Advanced Biomedical Image Analysis


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13146.69 руб.

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

Mark Haidekker Advanced Biomedical Image Analysis Mark Haidekker Advanced Biomedical Image Analysis
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Mark Haidekker Advanced Biomedical Image Analysis


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12673.31 руб.

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.

Sasu Tarkoma Publish / Subscribe Systems. Design and Principles Sasu Tarkoma Publish / Subscribe Systems. Design and Principles
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Sasu Tarkoma Publish / Subscribe Systems. Design and Principles


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9179.35 руб.

This book offers an unified treatment of the problems solved by publish/subscribe, how to design and implement the solutions In this book, the author provides an insight into the publish/subscribe technology including the design, implementation, and evaluation of new systems based on the technology. The book also addresses the basic design patterns and solutions, and discusses their application in practical application scenarios. Furthermore, the author examines current standards and industry best practices as well as recent research proposals in the area. Finally, necessary content matching, filtering, and aggregation algorithms and data structures are extensively covered as well as the mechanisms needed for realizing distributed publish/subscribe across the Internet. Key Features: Addresses the basic design patterns and solutions Covers applications and example cases including; combining Publish/Subscribe with cloud, Twitter, Facebook, mobile push (app store), Service Oriented Architecture (SOA), Internet of Things and multiplayer games Examines current standards and industry best practices as well as recent research proposals in the area Covers content matching, filtering, and aggregation algorithms and data structures as well as the mechanisms needed for realizing distributed publish/subscribe across the Internet Publish/Subscribe Systems will be an invaluable guide for graduate/postgraduate students and specialists in the IT industry, distributed systems and enterprise computing, software engineers and programmers working in social computing and mobile computing, researchers. Undergraduate students will also find this book of interest.

Ann Wheeler Standard and Super-Resolution Bioimaging Data Analysis. A Primer Ann Wheeler Standard and Super-Resolution Bioimaging Data Analysis. A Primer
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Ann Wheeler Standard and Super-Resolution Bioimaging Data Analysis. A Primer


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6748.95 руб.

A comprehensive guide to the art and science of bioimaging data acquisition, processing and analysis Standard and Super-Resolution Bioimaging Data Analysis gets newcomers to bioimage data analysis quickly up to speed on the mathematics, statistics, computing hardware and acquisition technologies required to correctly process and document data. The past quarter century has seen remarkable progress in the field of light microscopy for biomedical science, with new imaging technologies coming on the market at an almost annual basis. Most of the data generated by these systems is image-based, and there is a significant increase in the content and throughput of these imaging systems. This, in turn, has resulted in a shift in the literature on biomedical research from descriptive to highly-quantitative. Standard and Super-Resolution Bioimaging Data Analysis satisfies the demand among students and research scientists for introductory guides to the tools for parsing and processing image data. Extremely well illustrated and including numerous examples, it clearly and accessibly explains what image data is and how to process and document it, as well as the current resources and standards in the field. A comprehensive guide to the tools for parsing and processing image data and the resources and industry standards for the biological and biomedical sciences Takes a practical approach to image analysis to assist scientists in ensuring scientific data are robust and reliable Covers fundamental principles in such a way as to give beginners a sound scientific base upon which to build Ideally suited for advanced students having only limited knowledge of the mathematics, statistics and computing required for image data analysis An entry-level text written for students and practitioners in the bioscience community, Standard and Super-Resolution Bioimaging Data Analysis de-mythologises the vast array of image analysis modalities which have come online over the past decade while schooling beginners in bioimaging principles, mathematics, technologies and standards.

Vasileios Argyriou Image, Video and 3D Data Registration. Medical, Satellite and Video Processing Applications with Quality Metrics Vasileios Argyriou Image, Video and 3D Data Registration. Medical, Satellite and Video Processing Applications with Quality Metrics
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Vasileios Argyriou Image, Video and 3D Data Registration. Medical, Satellite and Video Processing Applications with Quality Metrics


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8998.6 руб.

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state-of-the-art registration methodologies used in a variety of targeted applications. Key features: Provides a state-of-the-art review of image and video registration techniques, allowing readers to develop an understanding of how well the techniques perform by using specific quality assessment criteria Addresses a range of applications from familiar image and video processing domains to satellite and medical imaging among others, enabling readers to discover novel methodologies with utility in their own research Discusses quality evaluation metrics for each application domain with an interdisciplinary approach from different research perspectives

Albalate Amparo Semi-Supervised and Unsupervised Machine Learning. Novel Strategies Albalate Amparo Semi-Supervised and Unsupervised Machine Learning. Novel Strategies
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Albalate Amparo Semi-Supervised and Unsupervised Machine Learning. Novel Strategies


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8790.39 руб.

This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic microarray data. Among those, the book focuses on a new application for dialog systems which can be thereby made adaptable and portable to different domains. Clustering evaluation metrics and new approaches, such as the ensembles of clustering algorithms, are also described.

McCann John J. The Art and Science of HDR Imaging McCann John J. The Art and Science of HDR Imaging
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McCann John J. The Art and Science of HDR Imaging


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11668.66 руб.

Rendering High Dynamic Range (HDR) scenes on media with limited dynamic range began in the Renaissance whereby painters, then photographers, learned to use low-range spatial techniques to synthesize appearances, rather than to reproduce accurately the light from scenes. The Art and Science of HDR Imaging presents a unique scientific HDR approach derived from artists’ understanding of painting, emphasizing spatial information in electronic imaging. Human visual appearance and reproduction rendition of the HDR world requires spatial-image processing to overcome the veiling glare limits of optical imaging, in eyes and in cameras. Illustrated in full colour throughout, including examples of fine-art paintings, HDR photography, and multiple exposure scenes; this book uses techniques to study the HDR properties of entire scenes, and measures the range of light of scenes and the range that cameras capture. It describes how electronic image processing has been used to render HDR scenes since 1967, and examines the great variety of HDR algorithms used today. Showing how spatial processes can mimic vision, and render scenes as artists do, the book also: Gives the history of HDR from artists' spatial techniques to scientific image processing Measures and describes the limits of HDR scenes, HDR camera images, and the range of HDR appearances Offers a unique review of the entire family of Retinex image processing algorithms Describes the considerable overlap of HDR and Color Constancy: two sides of the same coin Explains the advantages of algorithms that replicate human vision in the processing of HDR scenes Provides extensive data to test algorithms and models of vision on an accompanying website www.wiley.com/go/mccannhdr

Karl-Gunnar Olsson Structural Mechanics: Modelling and Analysis of Frames and Trusses Karl-Gunnar Olsson Structural Mechanics: Modelling and Analysis of Frames and Trusses
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Karl-Gunnar Olsson Structural Mechanics: Modelling and Analysis of Frames and Trusses


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4507.84 руб.

Textbook covers the fundamental theory of structural mechanics and the modelling and analysis of frame and truss structures Deals with modelling and analysis of trusses and frames using a systematic matrix formulated displacement method with the language and flexibility of the finite element method Element matrices are established from analytical solutions to the differential equations Provides a strong toolbox with elements and algorithms for computational modelling and numerical exploration of truss and frame structures Discusses the concept of stiffness as a qualitative tool to explain structural behaviour Includes numerous exercises, for some of which the computer software CALFEM is used. In order to support the learning process CALFEM gives the user full overview of the matrices and algorithms used in a finite element analysis

Ekins Sean Pharmaceutical Data Mining. Approaches and Applications for Drug Discovery Ekins Sean Pharmaceutical Data Mining. Approaches and Applications for Drug Discovery
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Ekins Sean Pharmaceutical Data Mining. Approaches and Applications for Drug Discovery


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12446.57 руб.

Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approaches for drug discovery—including chemogenomics, toxicogenomics, and individual drug response prediction. The five main sections of this volume cover: A general overview of the discipline, from its foundations to contemporary industrial applications Chemoinformatics-based applications Bioinformatics-based applications Data mining methods in clinical development Data mining algorithms, technologies, and software tools, with emphasis on advanced algorithms and software that are currently used in the industry or represent promising approaches In one concentrated reference, Pharmaceutical Data Mining reveals the role and possibilities of these sophisticated techniques in contemporary drug discovery and development. It is ideal for graduate-level courses covering pharmaceutical science, computational chemistry, and bioinformatics. In addition, it provides insight to pharmaceutical scientists, principal investigators, principal scientists, research directors, and all scientists working in the field of drug discovery and development and associated industries.

K. Thyagarajan S. Still Image and Video Compression with MATLAB K. Thyagarajan S. Still Image and Video Compression with MATLAB
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K. Thyagarajan S. Still Image and Video Compression with MATLAB


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10346.21 руб.

This book describes the principles of image and video compression techniques and introduces current and popular compression standards, such as the MPEG series. Derivations of relevant compression algorithms are developed in an easy-to-follow fashion. Numerous examples are provided in each chapter to illustrate the concepts.

Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis
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Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis


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3749.42 руб.

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.


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A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field. A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition Written by an expert team with accredited innovations in blind source separation and its applications in natural science Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.
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