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Author:
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 752
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Book Description
Author:
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 752
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Book Description
Author: International Geoscience and Remote Sensing Symposium (23, 2003, Toulouse)
Publisher:
ISBN:
Category :
Languages : en
Pages : 231
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Book Description
Author:
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 770
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Book Description
Author:
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 794
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Book Description
Author:
Publisher:
ISBN:
Category : Earth sciences
Languages : en
Pages : 788
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Book Description
Author:
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ISBN:
Category : Artificial satellites in earth sciences
Languages : en
Pages : 244
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Book Description
Author: Kusum Deep
Publisher: Springer Science & Business Media
ISBN: 8132204913
Category : Technology & Engineering
Languages : en
Pages : 1059
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Book Description
The objective is to provide the latest developments in the area of soft computing. These are the cutting edge technologies that have immense application in various fields. All the papers will undergo the peer review process to maintain the quality of work.
Author: Nicolas Ackermann
Publisher: Springer
ISBN: 3319131389
Category : Technology & Engineering
Languages : en
Pages : 323
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Book Description
"The PhD thesis written by Mr. Ackermann is an outstanding and in-depth scientific study that closes a research gap and paves the way to new developments. Despite the extremely complex issues, his work is very understandable and excellently elaborated." Prof. Dr. Christiane Schmullius "The PhD thesis written by Mr. Ackermann is an excellent and very comprehensive work performed at the highest scientific level. It examines in detail the potential of SAR data with regards to the derivation of forest stem volume in the temperate latitudes. The work belongs to a technically complex field. Nevertheless, Mr. Ackermann has succeeded in presenting the content in a clear and understandable way." Dr. Christian Thiel "The proposed document is overall of very good quality. Mr. Ackermann has done an exhaustive analysis of the in-situ data available on the Thuringian forest and was able to derive Growing Stocking Volume using L- and X-band spaceborne SAR data. The document is very well structured with a good split of information between the core of the text presented in the 6 chapters and the 4 annexes, which contain detailed results. Mr. Ackermann’s English grammar is excellent and his syntax is crystal clear, making his document pleasant to read. The way arguments are presented is logical and Mr. Ackermann gives a lot of attention to ensuring that sound explanations properly support these arguments." Dr. Maurice Borgeaud
Author: Gharoie Ahangar, Reza
Publisher: IGI Global
ISBN: 1668483882
Category : Business & Economics
Languages : en
Pages : 338
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Book Description
The relentless growth of data in financial markets has boosted the demand for more advanced analytical tools to facilitate and improve financial planning. The ability to constructively use this data is limited for managers and investors without the proper theoretical support. Within this context, there is an unmet demand for combining analytical finance methods with business analytics topics to inform better investment decisions. Advancement in Business Analytics Tools for Higher Financial Performance explores the financial applications of business analytics tools that can help financial managers and investors to better understand financial theory and improve institutional investment practices. This book explores the value extraction process using more accurate financial data via business analytical tools to help investors and portfolio managers develop more modern financial planning processes. Covering topics such as financial markets, investment analysis, and statistical tools, this book is ideal for accountants, data analysts, researchers, students, business professionals, academicians, and more.
Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 0470749008
Category : Technology & Engineering
Languages : en
Pages : 434
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Book Description
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.
