Supervised Multi-Task Learning for Tracking Inland Glacier Flows Using Sentinel-1 Tops Data

被引：0
|
作者：
Pulella, Andrea [1 ,2 ]
Sica, Francescopaolo [2 ]
Prats-Iraola, Pau [1 ]
机构：
[1] Microwaves and Radar Institute, German Aerospace Center (DLR), Germany
[2] University of the Bundeswehr, Institute of Space Technology and Space Applications, Munich, Germany
来源：
International Geoscience and Remote Sensing Symposium (IGARSS) | 2024年
关键词：
Convolutional neural networks - Deep neural networks - Image coding - Image segmentation - Interferometry - Multi-task learning - Self-supervised learning - Semi-supervised learning;
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页码：417 / 420
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