Improving Deep Learning-Based Height Estimation from Single SAR Images by Injecting Sensor Parameters
Author:
Affiliation:
1. University of the Bundeswehr Munich,Department of Aerospace Engineering,Neubiberg,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282228.pdf?arnumber=10282228
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1. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015,2015
2. Integrating Coordinate Features in CNN-Based Remote Sensing Imagery Classification
3. A 30 m global map of elevation with forests and buildings removed
4. Tunable U-Net: Controlling Image-to-Image Outputs Using a Tunable Scalar Value
5. SAR2HEIGHT: Height Estimation from a Single SAR Image in Mountain Areas via Sparse Height and Proxyless Depth-Aware Penalty Neural Architecture Search for Unet
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1. Deep Learning-Based Building Footprint Mapping Using High-Resolution SAR Data;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
2. The SAR2Height framework for urban height map reconstruction from single SAR intensity images;ISPRS Journal of Photogrammetry and Remote Sensing;2024-05
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