CRAUnet++: A New Convolutional Neural Network for Land Surface Water Extraction from Sentinel-2 Imagery by Combining RWI with Improved Unet++
Nan Li,
Xiaohua Xu,
Shifeng Huang
et al.
Abstract:Accurately mapping the surface water bodies through remote sensing technology is of great significance for water resources management, flood monitoring, and drought monitoring. At present, many scholars at home and abroad carry out research on deep learning image recognition algorithms based on convolutional neural networks, and a variety of variant-based convolutional neural networks are proposed to be applied to extract water bodies from remote sensing images. However, due to the low depth of convolutional l… Show more
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