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Distributed Processing of Large Remote Sensing Images Using Mapreduce

Advances in remote sensing technology and their ever increasing repositories of the collected data are revolutionizing the mechanisms these;

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Cloud Computing in Remote Sensing

remote sensing data integration across distributed data centers Covers cloud storage based remote sensing data share service Covers high;

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Deep Learning for Remote Sensing Images with Open Source Software

. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source;

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Deep Learning for Remote Sensing Images with Open Source Software

. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source;

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Data-Intensive Text Processing With MapReduce

requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed;

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Remote Sensing Imagery

Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle;

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Signal and Image Processing for Remote Sensing

of remote sensing signals and images Active learning methods in classification of remote sensing images Signal subspace identification;

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Hadoop: The Definitive Guide

Hadoop to build and maintain reliable, scalable, distributed systems. It's ideal for programmers looking to analyze datasets of any size, and for;

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Spectral Mixture for Remote Sensing

create fraction images. Chapter 6 offers remote sensing applications of fraction images in deforestation monitoring, burned-area mapping;

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Cognitive Networked Sensing and Big Data

Wireless Distributed Computing and Cognitive Sensing defines high-dimensional data processing in the context of wireless distributed;

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Hadoop in Action

HIGHLIGHT Hadoop in Action is an example-rich tutorial that shows developers how to implement data-intensive distributed;

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Remote Sensing Image Classification in R

This book offers an introduction to remotely sensed image processing and classification in R using machine learning algorithms. It also;

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Hbase in Action

run applications using HBase. First, it introduces the fundamentals of distributed systems and large scale data handling. Then, it explores;

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Introductory Remote Sensing Principles and Concepts

Introduction to Remote Sensing: Digital Image Processing and Applications presents a unique textbook/downloadable resources package. It;

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Computer Processing of Remotely-Sensed Images 5e

Computer Processing of Remotely-Sensed Images A thorough introduction to computer processing of remotely-sensed images, processing methods;

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High Performance Computing in Remote Sensing

Solutions for Time-Critical Remote Sensing Applications The recent use of latest-generation sensors in airborne and satellite platforms;

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High Performance Computing in Remote Sensing

Solutions for Time-Critical Remote Sensing Applications The recent use of latest-generation sensors in airborne and satellite platforms;

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Practical Handbook of Remote Sensing

including navigation, the transmission of data and satellite remote sensing; a space-based technology providing data accessible to everyone. The;

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Remote Sensing Digital Image Analysis

engaged in research using digital image analysis in remote sensing. The presentation level is for the mathematical non-specialist. Since the;

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Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning;

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Remote Sensing Time Series Image Processing

Today, remote sensing technology is an essential tool for understanding the Earth and managing human-Earth interactions. There is a rapidly;

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Introductory Remote Sensing Principles and Concepts

Introduction to Remote Sensing: Digital Image Processing and Applications presents a unique textbook/CD-ROM package. It explains;

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Polarimetric Radar Imaging

shows how to develop remote sensing applications using PolSAR imaging radar. The authors demonstrate how to devise intelligent information;

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Remote Sensing of Impervious Surfaces

Remote sensing of impervious surfaces has matured using advances in geospatial technology so recent that its applications have received;

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Remote Sensing of Landscapes with Spectral Images

Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge;

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Remote Sensing Of Landscapes With Spectral Images

Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge;

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Remote Sensing for Sustainability

using remote sensing; focuses on remote sensing methods and techniques for sustainable natural resources with emphasize on forests; answers;

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