5 pairs of fashionable multicolor stripe pattern socks for men



Носки MISHKA Printed Socks MAW183301F00 (Multicolor, O/S) Носки MISHKA Printed Socks MAW183301F00 (Multicolor, O/S) Новинка
Winifred Aldrich Metric Pattern Cutting for Women's Wear Winifred Aldrich Metric Pattern Cutting for Women's Wear Новинка

Winifred Aldrich Metric Pattern Cutting for Women's Wear

3426.72 руб. или Купить в рассрочку!
Metric Pattern Cutting for Women's Wear provides a straightforward introduction to the principles of form pattern cutting for garments to fit the body shape, and flat pattern cutting for casual garments and jersey wear. This sixth edition remains true to the original concept: it offers a range of good basic blocks, an introduction to the basic principles of pattern cutting and examples of their application into garments. Fully revised and updated to include a brand new and improved layout, up-to-date skirt and trouser blocks that reflect the changes in body sizing, along with updates to the computer-aided design section and certain blocks, illustrations and diagrams. This best-selling textbook still remains the essential purchase for students and beginners looking to understand pattern cutting and building confidence to develop their own pattern cutting style.
Чехол для iPhone 5 Stripe Cover розово-серебряный Чехол для iPhone 5 Stripe Cover розово-серебряный Новинка

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Puro Чехол для iPhone 5 Stripe Cover. Легкий пластиковый чехол с зеркальной поверхностью Puro Stripe Cover для iPhone 5 защитит устройство от пыли, грязи, пятен...
Bond Terry Computer-Aided Pattern Design and Product Development Bond Terry Computer-Aided Pattern Design and Product Development Новинка

Bond Terry Computer-Aided Pattern Design and Product Development

5277.19 руб. или Купить в рассрочку!
The use of computers has opened up remarkable opportunities for innovative design, improved productivity, and greater efficiency in the use of materials. Uniquely, this book focuses on the practical use of computers for clothing pattern design and product development. Readers are introduced to the various computer systems which are suitable for the industry, the principles and techniques of pattern design applied to computer systems are explained, and readers are shown how product data management can be used in clothing product development.
Mark Whistler Trading Pairs. Capturing Profits and Hedging Risk with Statistical Arbitrage Strategies Mark Whistler Trading Pairs. Capturing Profits and Hedging Risk with Statistical Arbitrage Strategies Новинка

Mark Whistler Trading Pairs. Capturing Profits and Hedging Risk with Statistical Arbitrage Strategies

8537.68 руб. или Купить в рассрочку!
An accessible guide to the pairs trading technique A leading arbitrage expert gives traders real tools for using pairs trading, including customizable Excel worksheets available on the companion website. Mark Whistler (Denver, CO) is the key developer of pairstrader.com as well as a licensed securities trader and broker and leading arbitrage expert.
Miller Daniel Au Pair Miller Daniel Au Pair Новинка

Miller Daniel Au Pair

5429.19 руб. или Купить в рассрочку!
Many families leave their children for years to be looked after by young people about whom they know next to nothing, from places they have barely heard of. Who are these au pairs, why do they come and what is their experience of this arrangement? Do they, for their part, find that they are treated as one of the family, and would they even want to be? After a year of careful research, this book shows how most of our assumptions and expectations about au pairs are wrong. This is the first book devoted to the lives of au pairs, their leisure as well as their work time. We see this world from the eyes of the visitors, and their unique perspective on what lies at the heart of our family life. The book does not flinch from documenting the realities of the situation Ð the racism and the problematic behaviour of the au pairs themselves, as much as the ignorance and exploitation they can be subject to. The book is a case study in how to come to feel modern life empathetically from the viewpoint of one of those many migrant groups we take for granted and rely on but rarely try to understand.
Mourad Elloumi Pattern Recognition in Computational Molecular Biology. Techniques and Approaches Mourad Elloumi Pattern Recognition in Computational Molecular Biology. Techniques and Approaches Новинка

Mourad Elloumi Pattern Recognition in Computational Molecular Biology. Techniques and Approaches

10640.71 руб. или Купить в рассрочку!
A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
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Jan Flusser Moments and Moment Invariants in Pattern Recognition Jan Flusser Moments and Moment Invariants in Pattern Recognition Новинка

Jan Flusser Moments and Moment Invariants in Pattern Recognition

Moments as projections of an image’s intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms – translation, rotation, scaling, and affine transform – from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.
Webb Andrew R. Statistical Pattern Recognition Webb Andrew R. Statistical Pattern Recognition Новинка

Webb Andrew R. Statistical Pattern Recognition

11719.91 руб. или Купить в рассрочку!
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields, including the areas of engineering, statistics, computer science and the social sciences. The book has been updated to cover new methods and applications, and includes a wide range of techniques such as Bayesian methods, neural networks, support vector machines, feature selection and feature reduction techniques.Technical descriptions and motivations are provided, and the techniques are illustrated using real examples. Statistical Pattern Recognition, 3rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition monitoring. Provides descriptions and guidance for implementing techniques, which will be invaluable to software engineers and developers seeking to develop real applications Describes mathematically the range of statistical pattern recognition techniques. Presents a variety of exercises including more extensive computer projects. The in-depth technical descriptions make the book suitable for senior undergraduate and graduate students in statistics, computer science and engineering. Statistical Pattern Recognition is also an excellent reference source for technical professionals. Chapters have been arranged to facilitate implementation of the techniques by software engineers and developers in non-statistical engineering fields. www.wiley.com/go/statistical_pattern_recognition
Elaine Knuth Trading Between the Lines. Pattern Recognition and Visualization of Markets Elaine Knuth Trading Between the Lines. Pattern Recognition and Visualization of Markets Новинка

Elaine Knuth Trading Between the Lines. Pattern Recognition and Visualization of Markets

3880.76 руб. или Купить в рассрочку!
Insights into a pattern-based method of trading that can increase the likelihood of profitable outcomes While most books on chart patterns, or pattern recognition, offer detailed discussion and analysis of one type of pattern, the fact is that a single pattern may not be very helpful for trading, since it often does not give a complete picture of the market. What sets Trading Between the Lines apart from other books in this area is author Elaine Knuth's identification of sets of patterns that give a complete analysis of the market. In it, she identifies more complex chart patterns, often several patterns combined over multiple time frames, and skillfully examines these sets of patterns called «constellations» in relation to one another. These constellations turn sets of individual patterns into a more manageable set of patterns, where the relationship between them can lead to tactical trading opportunities. Shows how to apply complex patterns to specific trades and identify opportunities as well entry and exit points Markets covered include commodities, equities, and indexes Presents an effective trading approach based on real market cycles-as opposed to computer simulations-that are found in active markets Moving beyond the simple identification of basic patterns to identifying pattern constellations, this reliable resource will give you a better view of what is really going on in the market and help you profit from the opportunities you uncover.
Ludmila Kuncheva I. Combining Pattern Classifiers. Methods and Algorithms Ludmila Kuncheva I. Combining Pattern Classifiers. Methods and Algorithms Новинка

Ludmila Kuncheva I. Combining Pattern Classifiers. Methods and Algorithms

8664.87 руб. или Купить в рассрочку!
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods. Thoroughly updated, with MATLAB® code and practice data sets throughout, Combining Pattern Classifiers includes: Coverage of Bayes decision theory and experimental comparison of classifiers Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others Chapters on classifier selection, diversity, and ensemble feature selection With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.
Edward R. Dougherty Error Estimation for Pattern Recognition Edward R. Dougherty Error Estimation for Pattern Recognition Новинка

Edward R. Dougherty Error Estimation for Pattern Recognition

10261.41 руб. или Купить в рассрочку!
This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition. Ulisses M. Braga Neto is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, USA. He received his PhD in Electrical and Computer Engineering from The Johns Hopkins University. Dr. Braga Neto received an NSF CAREER Award for his work on error estimation for pattern recognition with applications in genomic signal processing. He is an IEEE Senior Member. Edward R. Dougherty is a Distinguished Professor, Robert F. Kennedy ’26 Chair, and Scientific Director at the Center for Bioinformatics and Genomic Systems Engineering at Texas A&M University, USA. He is a fellow of both the IEEE and SPIE, and he has received the SPIE Presidents Award. Dr. Dougherty has authored several books including Epistemology of the Cell: A Systems Perspective on Biological Knowledge and Random Processes for Image and Signal Processing (Wiley-IEEE Press).
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кассеты DEONICA For Men 5 лезвий 4шт.

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Jennifer Lynne Matthews-Fairbanks Bare Essentials. Bras - Second Edition: Construction and Pattern Drafting for Lingerie Design Jennifer Lynne Matthews-Fairbanks Bare Essentials. Bras - Second Edition: Construction and Pattern Drafting for Lingerie Design Новинка

Jennifer Lynne Matthews-Fairbanks Bare Essentials. Bras - Second Edition: Construction and Pattern Drafting for Lingerie Design

This is the second edition. Instructions have been clarified in the drafting section and additional drafting and grading directions are provided with the use of computer aided design.The Bare Essentials series is an invaluable resource for anyone entering into the field of lingerie design. This volume summarizes the basics of bra design, from sewing and construction to drafting and pattern grading; introducing these subjects in a manageable capacity. Bare Essentials is organized into three main sections based on the complexities of the information provided. Included in this book are basic patterns for sizes 30A-40F.What you will learn:• Construction methods using elastics and stretch fabrics• Manipulation of basic patterns• Pattern drafting from measurements• Developing grade rules and grading patterns• Drafting and grading on the computer
Maron Mays BrownCalderwood Atlas for the Diagnosis of Tumors in the Dog and Cat Maron Mays BrownCalderwood Atlas for the Diagnosis of Tumors in the Dog and Cat Новинка

Maron Mays BrownCalderwood Atlas for the Diagnosis of Tumors in the Dog and Cat

9499.92 руб. или Купить в рассрочку!
Atlas for the Diagnosis of Tumors in the Dog and Cat is a diagnostic tool for determining if samples are abnormal and defining the cause of the abnormality, with 386 clinical images depicting normal and abnormal results. Offers a brief overview of the methods used to produce a diagnosis and prognosis from a biopsy tissue sample Pairs photographs of biopsy samples with photomicrographs of cells obtained via fine needle aspirate Includes a useful chapter covering sample handling, staining, and shipping
Richard Brereton G. Chemometrics for Pattern Recognition Richard Brereton G. Chemometrics for Pattern Recognition Новинка

Richard Brereton G. Chemometrics for Pattern Recognition

12161.54 руб. или Купить в рассрочку!
Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; Representation in full colour; Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.
Richard Brereton G. Chemometrics for Pattern Recognition Richard Brereton G. Chemometrics for Pattern Recognition Новинка

Richard Brereton G. Chemometrics for Pattern Recognition

12418.44 руб. или Купить в рассрочку!
Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; Representation in full colour; Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.

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This book is the first of its kind to discuss error estimation with a model-based approach. From the basics of classifiers and error estimators to distributional and Bayesian theory, it covers important topics and essential issues pertaining to the scientific validity of pattern classification. Error Estimation for Pattern Recognition focuses on error estimation, which is a broad and poorly understood topic that reaches all research areas using pattern classification. It includes model-based approaches and discussions of newer error estimators such as bolstered and Bayesian estimators. This book was motivated by the application of pattern recognition to high-throughput data with limited replicates, which is a basic problem now appearing in many areas. The first two chapters cover basic issues in classification error estimation, such as definitions, test-set error estimation, and training-set error estimation. The remaining chapters in this book cover results on the performance and representation of training-set error estimators for various pattern classifiers. Additional features of the book include: • The latest results on the accuracy of error estimation • Performance analysis of re-substitution, cross-validation, and bootstrap error estimators using analytical and simulation approaches • Highly interactive computer-based exercises and end-of-chapter problems This is the first book exclusively about error estimation for pattern recognition. Ulisses M. Braga Neto is an Associate Professor in the Department of Electrical and Computer Engineering at Texas A&M University, USA. He received his PhD in Electrical and Computer Engineering from The Johns Hopkins University. Dr. Braga Neto received an NSF CAREER Award for his work on error estimation for pattern recognition with applications in genomic signal processing. He is an IEEE Senior Member. Edward R. Dougherty is a Distinguished Professor, Robert F. Kennedy ’26 Chair, and Scientific Director at the Center for Bioinformatics and Genomic Systems Engineering at Texas A&M University, USA. He is a fellow of both the IEEE and SPIE, and he has received the SPIE Presidents Award. Dr. Dougherty has authored several books including Epistemology of the Cell: A Systems Perspective on Biological Knowledge and Random Processes for Image and Signal Processing (Wiley-IEEE Press).
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