Uncertainty Assessment of Hyperspectral Image Classification: Deep Learning vs. Random Forest

Uncertainty Assessment of Hyperspectral Image Classification: Deep Learning vs. Random Forest

Uncertainty assessment techniques have been extensively applied as an estimate of accuracy to compensate for weaknesses with traditional approaches. Traditional approaches to mapping accuracy assessment have been based on a confusion matrix, and hence are not only dependent on the availability of te...

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Bibliographic Details
Main Authors: Majid Shadman Roodposhti, Jagannath Aryal, Arko Lucieer, Brett A. Bryan
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Entropy
Subjects:
uncertainty assessment
deep neural network
random forest
Shannon entropy
Online Access:http://www.mdpi.com/1099-4300/21/1/78

Internet

http://www.mdpi.com/1099-4300/21/1/78

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