A CNN-based Sentinel-2 image super-resolution method using multiobjective training
Deep learning methods have become ubiquitous tools in many Earth observation
applications, delivering state-of-the-art results while proving to generalize for a variety of …
applications, delivering state-of-the-art results while proving to generalize for a variety of …
Machine learning for Arctic sea ice physical properties estimation using dual-polarimetric SAR data
This work introduces a novel method that combines machine learning (ML) techniques with
dual-polarimetric (dual-pol) synthetic aperture radar (SAR) observations for estimating quad …
dual-polarimetric (dual-pol) synthetic aperture radar (SAR) observations for estimating quad …
[PDF][PDF] Research on SAR image object/land fine interpretation methods
J Zhao - 2020 - elib.dlr.de
摘要合成孔径雷达 (Synthetic Aperture Radar, SAR) 由于具有全天时全天候对地观测能力,
较强的穿透能力, 以及极化信息获取能力, 在军事和民用领域中均得到了广泛的研究与应用. SAR …
较强的穿透能力, 以及极化信息获取能力, 在军事和民用领域中均得到了广泛的研究与应用. SAR …
Comparison of Machine Learning Methods for Predicting Quad-Polarimetric Parameters from Dual-Polarimetric Sar Data
K Blix, MM Espeseth, T Eltaft - IGARSS 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
This work evaluates three machine learning methods with respect to their ability of learning
the functional relationship between dual-polarimetric (dual-pol) input data and quad …
the functional relationship between dual-polarimetric (dual-pol) input data and quad …