New PDF release: Computational Intelligence for Remote Sensing

By X. Prieto-Blanco, C. Montero-Orille (auth.), Manuel Graña, Richard J. Duro (eds.)

ISBN-10: 3540793526

ISBN-13: 9783540793526

This publication is a composition of other issues of view concerning the program of Computational Intelligence recommendations and strategies to distant Sensing information and functions. it's the basic consensus that type, its similar information processing, and international optimization tools are middle subject matters of Computational Intelligence. a lot of the content material of the e-book is dedicated to photograph segmentation and popularity, utilizing assorted instruments from various components of the Computational Intelligence box, starting from synthetic Neural Networks to Markov Random box modeling. The e-book covers a vast variety of issues, ranging from the layout of hyperspectral sensors, and knowledge dealing with difficulties, specifically facts compression and watermarking matters, in addition to self reliant net companies. the most contents of the ebook are dedicated to photograph research and effective (parallel) implementations of those research ideas. The sessions of pictures handled through the ebook are in most cases multispectral-hyperspectral pictures, even though there are a few circumstances of processing man made Aperture Radar images.

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Extra info for Computational Intelligence for Remote Sensing

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Human Centred A human centric system must support semantic interactions. This requires the coding of specific data, information and knowledge. The coding must also support computer processes like automatic checking or reasoning. Users In KEO, two types of external users are addressed: • Remote Sensing Expert, with EO, signal and image processing know-how, using KEO to create FEPs for new information mining capabilities. • Domain Expert, not necessarily an EO, using KEO to interactively explore a collection of images or to run an available FEP against own images.

The prime objective of the use of Open Standards is interoperability. The EIF [24] formulates interoperability as “the ability of information and communication technology (ICT) systems and of the business processes they support to exchange data and to enable the sharing of information and knowledge”. In other words, interoperability is the fact of letting different systems developed by different suppliers co-operate together by employing common definitions, information models, encodings and interfaces.

The first type includes methods that are specific for each feature (usually involving the analysis of pixels, looking for a predefined pattern) and therefore more robust and precise. These methods can provide fully or partially automatic information extraction (partially when the user must intervene to define parameters or take decisions). The second type is more generic. It works by extracting and storing the basic characteristics of image pixels and areas during the ingestion of a set of images. The user then trains the system by selecting the representative basic characteristics from sample images.

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Computational Intelligence for Remote Sensing by X. Prieto-Blanco, C. Montero-Orille (auth.), Manuel Graña, Richard J. Duro (eds.)

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