Application of Deep Learning in the Processing of the Aerospace System's Multispectral Images
Autor: | Andrii Podorozhniak, Daria Hlavcheva, Vladyslav Yaloveha, Heorhii Kuchuk |
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Rok vydání: | 2020 |
Předmět: |
010304 chemical physics
business.industry Computer science Deep learning Multispectral image 0211 other engineering and technologies 02 engineering and technology 01 natural sciences 0103 physical sciences Computer vision Artificial intelligence business Aerospace 021101 geological & geomatics engineering |
DOI: | 10.4018/978-1-7998-1415-3.ch005 |
Popis: | This chapter uses deep learning neural networks for processing of aerospace system multispectral images. Convolutional and Capsule Neural Network were used for processing multispectral images from satellite Landsat 8, previously processed using spectral indices NDVI, NDWI, PSRI. The authors' approach was applied to wildfire Camp Fire (California, USA). The deep learning neural networks are used to solve the problem of detecting fire hazardous forest areas. Comparison of Convolutional and Capsule Neural Network results was done. The theory of neural networks of deep learning, the theory of recognition of multispectral images, methods of mathematical statistics were used. |
Databáze: | OpenAIRE |
Externí odkaz: |
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