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Author:
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ISBN:
Category : Mineral industries
Languages : en
Pages : 220
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Author:
Publisher:
ISBN:
Category : Mineral industries
Languages : en
Pages : 220
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Book Description
Author:
Publisher:
ISBN:
Category : Mineral industries
Languages : en
Pages : 296
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Author: Charles George Warnford Lock
Publisher:
ISBN:
Category : Gold
Languages : en
Pages : 858
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Author:
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ISBN:
Category : Mineral industries
Languages : en
Pages : 564
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Author:
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ISBN:
Category : Mines and mineral resources
Languages : en
Pages : 300
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Author:
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ISBN:
Category : Mines and mineral resources
Languages : en
Pages : 436
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Author: Florin Gorunescu
Publisher: Springer Science & Business Media
ISBN: 3642197213
Category : Technology & Engineering
Languages : en
Pages : 364
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Book Description
The knowledge discovery process is as old as Homo sapiens. Until some time ago this process was solely based on the ‘natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since “knowledge is power”. The goal of this book is to provide, in a friendly way, both theoretical concepts and, especially, practical techniques of this exciting field, ready to be applied in real-world situations. Accordingly, it is meant for all those who wish to learn how to explore and analysis of large quantities of data in order to discover the hidden nugget of information.
Author: Nagiza F. Samatova
Publisher: CRC Press
ISBN: 1439860858
Category : Business & Economics
Languages : en
Pages : 495
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Book Description
Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or cluste
Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 1351673289
Category : Technology & Engineering
Languages : en
Pages : 612
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Book Description
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.
Author:
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ISBN:
Category : Coal mines and mining
Languages : en
Pages : 618
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