Deep learning classifiers for hyperspectral imaging: A review
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Abstract
Advances in computing technology have fostered the development of new and powerful deep learning (DL) techniques, which have demonstrated promising results in a wide range of applications. Particularly, DL methods have been successfully used to classify remotely sensed data collected by Earth Observation (EO) instruments. Hyperspectral imaging (HSI) is a hot topic in remote sensing data analysis due to the vast amount of information comprised by this kind of images, which allows for a better characterization and exploitation of the Earth surface by combining rich spectral and spatial information. However, HSI poses major challenges for supervised classification methods due to the high dimensionality of the…
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Keywords
- Hyperspectral imaging
- Computer science
- Artificial intelligence
- Deep learning
- Pattern recognition (psychology)
- Earth observation
- Machine learning
- Remote sensing
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