Since the publishing of the first edition of Classification Methods for Remotely Sensed Data in 2001, the field of pattern recognition has expanded in many new directions that make use of new technologies to capture data and more powerful computers to mine and process it. What seemed visionary but a decade ago is now being put to use and refined in commercial applications as well as military ones. Keeping abreast of these new developments, Classification Methods for Remotely Sensed Data, Second Edition provides a ...
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Since the publishing of the first edition of Classification Methods for Remotely Sensed Data in 2001, the field of pattern recognition has expanded in many new directions that make use of new technologies to capture data and more powerful computers to mine and process it. What seemed visionary but a decade ago is now being put to use and refined in commercial applications as well as military ones. Keeping abreast of these new developments, Classification Methods for Remotely Sensed Data, Second Edition provides a comprehensive and up-to-date review of the entire field of classification methods applied to remotely sensed data. This second edition provides seven fully revised chapters and two new chapters covering support vector machines (SVM) and decision trees. It includes updated discussions and descriptions of Earth observation missions along with updated bibliographic references. After an introduction to the basics, the text provides a detailed discussion of different approaches to image classification, including maximum likelihood, fuzzy sets, and artificial neural networks. This cutting-edge resource: Presents a number of approaches to solving the problem of allocation of data to one of several classes Covers potential approaches to the use of decision trees Describes developments such as boosting and random forest generation Reviews lopping branches that do not contribute to the effectiveness of the decision trees Complete with detailed comparisons, experimental results, and discussions for each classification method introduced, this book will bolster the work of researchers and developers by giving them access to new developments. It also provides students with a solid foundation in remote sensing data classification methods.
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Seller's Description:
This is an ex-library book and may have the usual library/used-book markings inside. This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item, 750grams, ISBN: 9781420090727.
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Seller's Description:
Like New. Boards have light surface wear, small inked out sticker inside front board, otherwise boards and pages are Clean and bright! Overall in Great condition! (1.2M-1S)
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Seller's Description:
Very Good++; Hardcover; Close to new condition; Covers are still glossy with "straight" edge-corners; Unblemished textblock edges; The endpapers and all text pages are bright and unmarked; Binding is tight with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (8.5Äù Äì 9.75Äù tall); Black covers with title in light green lettering; 2nd Edition; 2009, CRC Press; 376 pages; "Classification Methods for Remotely Sensed Data, Second Edition, " by Paul Mather & Brandt Tso.