NNetEn<sub>2D</sub>: Two-Dimensional Neural Network Entropy in Remote Sensing Imagery and Geophysical Mapping

NNetEn<sub>2D</sub>: Two-Dimensional Neural Network Entropy in Remote Sensing Imagery and Geophysical Mapping

Measuring the predictability and complexity of 2D data (image) series using entropy is an essential tool for evaluation of systems’ irregularity and complexity in remote sensing and geophysical mapping. However, the existing methods have some drawbacks related to their strong dependence on method pa...

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Bibliographic Details
Main Authors: Andrei Velichko, Matthias P. Wagner, Alireza Taravat, Bruce Hobbs, Alison Ord
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Remote Sensing
Subjects:
2D entropy
NNetEn
time series
data series
neural network
MNIST-10
Online Access:https://www.mdpi.com/2072-4292/14/9/2166

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