Jan 23, 2023 · This article proposes a new model-adaptive network (MAda-Net) to implement deep-learning-based TomoSAR 3-D imaging with a much improved processing accuracy.

The compressive sensing (CS)-based tomographic SAR (TomoSAR) 3-D imaging method has the shortcoming of low efficiency, mainly represented in two aspects: ...

This paper proposes a new model-adaptive network. (MAda-Net) to implement deep learning based TomoSAR 3D imaging with a much improved processing accuracy. First ...

Abstract ; Publication: IEEE Transactions on Geoscience and Remote Sensing ; Pub Date: 2023 ; DOI: 10.1109/TGRS.2023.3239405 ; Bibcode: 2023ITGRS..6139405W.

IEEE Transactions on Geoscience and Remote Sensing, volume 61, pages 1-13. MAda-Net: Model-Adaptive Deep Learning Imaging for SAR Tomography. Yan Wang 1.

MAda-Net: Model-Adaptive Deep Learning Imaging for SAR Tomography. Y. Wang, C. Liu, R. Zhu, M. Liu, Z. Ding, and T. Zeng. IEEE Trans. Geosci. Remote.

Dive into the research topics of 'MAda-Net: Model-Adaptive Deep Learning Imaging for SAR Tomography'. Together they form a unique fingerprint. Sort by; Weight ...

基于压缩感知（CS）的层析合成孔径雷达（TomoSAR）三维成像方法存在效率低下的缺点，主要表现在两个方面：首先，CS求解器需要迭代计算，因此计算量大；其次，CS 求解器需要 ...

MAda-Net: Model-Adaptive Deep Learning Imaging for SAR Tomography. Yan Wang Changhao Liu Rui Zhu Minkun Liu Zegang Ding Tao Zeng. Published in: IEEE Trans.

This paper describes a deep learning approach, named Tomographic SAR Neural Network ... MAda-Net: Model-Adaptive Deep Learning Imaging for SAR Tomography. Article.