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Found 10 papers, 0 papers with code
Shadow-Oriented Tracking Method for Multi-Target Tracking in Video-SAR
To avoid missed tracking, a detection method based on deep learning is designed to thoroughly learn shadows' features, thus increasing the accurate estimation.
Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework
Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the task's specific demands well.
Near-filed SAR Image Restoration with Deep Learning Inverse Technique: A Preliminary Study
Adhering to it, a model-based deep learning network is designed to restore the image.
A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging
To address that, we propose a new model-data-driven network to achieve tomoSAR imaging based on multi-dimensional features.
Sar Ship Detection based on Swin Transformer and Feature Enhancement Feature Pyramid Network
Swin Transformer serves as backbone to model long-range dependencies and generates hierarchical features maps.
3D Super-Resolution Imaging Method for Distributed Millimeter-wave Automotive Radar System
In this paper, a new distributed mmW radar system is designed to solve this problem.
Constant-Time-Delay Interferences In Near-Field SAR: Analysis And Suppression In Image Domain
To bridge this gap, in the first time, analysis and the suppression method of interferences in near-field SAR are presented in this work.
Near-Field SAR Image Restoration Based On Two Dimensional Spatial-Variant Deconvolution
To ease this restriction, in this work an image restoration method based on the 2D spatial-variant deconvolution is proposed.
Two Dimensional Sparse-Regularization-Based InSAR Imaging with Back-Projection Embedding
First, to enhance the imaging quality, we propose a new imaging framework base on 2D sparse regularization, where the characteristic of scene is embedded.
Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images
Huge imbalance of different scenes' sample numbers seriously reduces Synthetic Aperture Radar (SAR) ship detection accuracy.
