Könyv Automatic Hyperspectral Data Analysis Sildomar Monteiro

Automatic Hyperspectral Data Analysis

A machine learning approach to high dimensional feature extraction

Nyelv: Angol
Kötés: Puha kötésű
Kiadó: VDM Verlag
Elérhetőség: Beszállítói készleten
Küldés 9-15 napon belül
19 081 Ft
Advances in spectroscopy sensors have allowed the acquisition of ever-increasing volumes of data fro...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
108
EAN
9783639255164
ISBN
363925516X
Enbook ID
06832967
Kiadó
Súly
168
Méretek
152 x 229 x 7

Teljes leírás

Advances in spectroscopy sensors have allowed the acquisition of ever-increasing volumes of data from scenes, either remotely, by air- or space-borne devices, or locally, by hand-held spectrometers or stand-alone cameras. With this boom in the amount of data available has also come a greater need for extracting useful information efficiently and for developing automated methods for novel applications. Traditional approaches to spectral analysis often require a great deal of human effort and prior knowledge, and have difficulty in processing high dimensional data sets provided by new sensors. This book, therefore, provides an alternative approach to select relevant features from hyperspectral data utilizing machine learning to automate the analysis. The methods are developed in the context of two applications: in biomedical imaging and in precision agriculture. The techniques discussed should be useful to graduate students and researchers in computer science and engineering interested in hyperspectral imaging, remote sensing or optimization for high dimensional data.

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