Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling

Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling

Hyperspectral imaging is a rich source of data, allowing for a multitude of effective applications. However, such imaging remains challenging because of large data dimension and, typically, a small pool of available training examples. While deep learning approaches have been shown to be successful i...

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Bibliographic Details
Main Authors: Wojciech Masarczyk, Przemysław Głomb, Bartosz Grabowski, Mateusz Ostaszewski
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
hyperspectral image classification
deep learning
convolutional neural networks
transfer learning
unsupervised training sample selection
Online Access:https://www.mdpi.com/2072-4292/12/16/2653

Internet

https://www.mdpi.com/2072-4292/12/16/2653

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