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
Rezensionen / Stimmen
... a very useful addition to the shelf of anyone engaged in remote sensing image analysis. It is suitable for both students and practitioners.-Michael Collins, in GEOMATICA, Vol. 63, No. 4 ... a very useful addition to the shelf of anyone engaged in remote sensing image analysis. It is suitable for both students and practitioners.-Michael Collins, in GEOMATICA, Vol. 63, No. 4
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Graduate and doctoral students working with remote sensing data in digital image analysis and GIS environments.
Editions-Typ
Illustrationen
195 s/w Abbildungen, 18 s/w Tabellen
195 b/w images, 18 tables and 396 equations
ISBN-13
978-1-4200-9074-1 (9781420090741)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Remote Sensing in the Optical and Microwave Regions. Pattern Recognition Principles. Artificial Neural Networks. Support Vector Machines. Methods Based on Fuzzy Set Theory. Decision Trees. Texture Quantization. Modeling Context Using Markov Random Fields. Multisource Classification. Bibliography. Index.
