Supervised Classification of Multisensor Remotely Sensed Images Using a Deep Learning Framework

Supervised Classification of Multisensor Remotely Sensed Images Using a Deep Learning Framework

In this paper, we present a convolutional neural network (CNN)-based method to efficiently combine information from multisensor remotely sensed images for pixel-wise semantic classification. The CNN features obtained from multiple spectral bands are fused at the initial layers of deep neural network...

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Bibliographic Details
Main Authors: Sankaranarayanan Piramanayagam, Eli Saber, Wade Schwartzkopf, Frederick W. Koehler
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Remote Sensing
Subjects:
image classification
deep learning
multisensor data
sentinel data
Online Access:http://www.mdpi.com/2072-4292/10/9/1429

Internet

http://www.mdpi.com/2072-4292/10/9/1429

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