Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation, Thenkabail, Prasad S.
Автор: Werner Dubitzky; Martin Granzow; Daniel P. Berrar Название: Fundamentals of Data Mining in Genomics and Proteomics ISBN: 1441942912 ISBN-13(EAN): 9781441942913 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics.
Название: Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation ISBN: 1138058548 ISBN-13(EAN): 9781138058545 Издательство: Taylor&Francis Рейтинг: Цена: 158230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses both the strengths and the limitations of the topics covered: (a) hyperspectral processes, (b) sensors, and (c) data analysis. Each chapter reviews existing "state-of-art" knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral data in study of vegetation and its numerous applications.
Автор: Zhang Dengsheng Название: Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval ISBN: 3030692507 ISBN-13(EAN): 9783030692506 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Поставка под заказ. Описание: 1. Fourier Transform.- 2. Windowed Fourier Transform.- 3. Wavelet Transform.- 4. Color Feature Extraction.- 5. Texture Feature Extraction.- 6. Shape Representation.- 7. Bayesian Classification.- Support Vector Machines.- 8. Artificial Neural Networks.- 9. Image Annotation with Decision Trees.-10. Image Indexing.- 11. Image Ranking.- 12. Image Presentation.- 13. Appendix.
Автор: Andrade Название: Fundamentals of Stream Processing ISBN: 1107015545 ISBN-13(EAN): 9781107015548 Издательство: Cambridge Academ Рейтинг: Цена: 91870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book teaches fundamentals of the stream processing paradigm that addresses performance, scalability and usability challenges in extracting insights from massive amounts of live, streaming data. It presents core principles behind application design, system infrastructure and analytics, coupled with real-world examples for a comprehensive understanding of the stream processing area.
Автор: Graham Pryor, Sarah Jones, Angus Whyte Название: Delivering Research Data Management Services: Fundamentals of Good Practice ISBN: 1783303077 ISBN-13(EAN): 9781783303076 Издательство: Facet Рейтинг: Цена: 211200.00 T Наличие на складе: Невозможна поставка. Описание: This groundbreaking guide will lead researchers, institutions and policy makers through the processes needed to set up and run effective institutional research data management services to support their researchers and networks.
Автор: Dengsheng Zhang Название: Fundamentals of Image Data Mining ISBN: 3030179885 ISBN-13(EAN): 9783030179885 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Поставка под заказ. Описание: This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.
Автор: Lars Elden Название: Matrix Methods in Data Mining and Pattern Recognition ISBN: 1611975859 ISBN-13(EAN): 9781611975857 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 65610.00 T Наличие на складе: Невозможна поставка. Описание: Provides an updated treatment of numerical linear algebra techniques for solving problems in data mining and pattern recognition. Adopting an application-oriented approach, the author introduces matrix theory and decompositions, describes how modern matrix methods can be applied in real life scenarios.
Автор: Pfadenhauer Jцrg S., Klцtzli Frank A. Название: Global Vegetation: Fundamentals, Ecology and Distribution ISBN: 303049859X ISBN-13(EAN): 9783030498597 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Поставка под заказ. Описание: This up-to-date textbook of global vegetation ecology, which comprises the current state of knowledge, is long overdue and much-needed. It is a translation of the textbook “Vegetation der Erde” (Springer-Spektrum, Heidelberg). A short introductory chapter deals with the fundamentals of vegetation ecology that are of importance for the delimitation and characterization of the global vegetation presented in this book (chorology, evolution of plants, physiognomic and structural characteristics, phytodiversity and the human impact on it as well as general terminology concerning both plant growth forms and on vegetation structure types). In the following chapters the zonal and azonal vegetation from the tropics to the polar regions including high mountains is described and discussed. The main focus is on the characterization of interactions between the spatial location of plants and plant communities on the one hand and site conditions, historic and genetic processes, spatial and temporal patterns, ecophysiology and anthropogenic influences on the other hand. Additional information on specific topics is provided in 51 boxes.
Автор: Zhang Dengsheng Название: Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval ISBN: 3030179915 ISBN-13(EAN): 9783030179915 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods;
Автор: Katharina Morik, Peter Marwedel Название: Fundamentals ISBN: 3110785935 ISBN-13(EAN): 9783110785937 Издательство: Walter de Gruyter Рейтинг: Цена: 142510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are executed on diverse architectures to save resources. It provides a comprehensive overview of the novel approaches to machine learning research that consider resource constraints, as well as the application of the described methods in various domains of science and engineering.
Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to the different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Several machine learning methods are inspected with respect to their resource requirements and how to enhance their scalability on diverse computing architectures ranging from embedded systems to large computing clusters.
Автор: Lars Eld?n Название: Matrix Methods in Data Mining and Pattern Recognition ISBN: 0898716268 ISBN-13(EAN): 9780898716269 Издательство: Cambridge Academ Рейтинг: Цена: 60190.00 T Наличие на складе: Поставка под заказ. Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.
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