State-of-the-Art Capability of Convolutional Neural Networks to Distinguish the Signal in the Ionosphere

Recovering and distinguishing different ionospheric layers and signals usually requires slow and complicated procedures. In this work, we construct and train five convolutional neural network (CNN) models: DeepLab, fully convolutional DenseNet24 (FC-DenseNet24), deep watershed transform (DWT), Mask...

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Autors principals:	Yu-Chi Chang, Chia-Hsien Lin, Alexei V. Dmitriev, Mon-Chai Hsieh, Hao-Wei Hsu, Yu-Ciang Lin, Merlin M. Mendoza, Guan-Han Huang, Lung-Chih Tsai, Yung-Hui Li, Enkhtuya Tsogtbaatar
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-04-01
Col·lecció:	Sensors
Matèries:	ionospheric sounding artificial intelligence image segmentation
Accés en línia:	https://www.mdpi.com/1424-8220/22/7/2758
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