Combining Contextual Information by Integrated Attention Mechanism in Convolutional Neural Networks for Digital Elevation Model Super-Resolution

High-resolution digital elevation models (HR DEMs) can provide accurate geographic information, which is widely used in flood risk evaluation, hazard mapping, and hydrological modeling. The study of DEM super-resolution (SR) algorithms has relieved the need for HR DEMs. However, most CNN backbone ne...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on geoscience and remote sensing Ročník 62; s. 1 - 16
Hlavní autoři:	Chen, Zhanlong, Han, Xiaoyi, Ma, Xiaochuan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Artificial neural networks Attention Attention mechanism Attention mechanisms contextual information Convolution Convolutional neural networks Deep learning Deformation effects dependence of long-range geographical features digital elevation model super-resolution (DEM SR) Digital Elevation Models Elevation Encoders-Decoders Environmental risk Feature extraction Formability Information processing Machine learning Modules Neural networks Ridges Risk assessment Rivers Superresolution Task analysis
ISSN:	0196-2892, 1558-0644
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!