most citedA generative approach for lensless imaging in low-light conditions

12 citations · 12 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2025

Large-field-of-view lensless imaging with miniaturized sensors

Yu Ren, Xiaoling Zhang, Xu Zhan +4

Lensless cameras replace bulky optics with thin modulation masks, enabling compact imaging systems. However, existing methods rely on an idealized model that assumes a globally shi…

eess.IV2025★ 12 cited

A generative approach for lensless imaging in low-light conditions

Ziyang Liu, Tianjiao Zeng, Xu Zhan +2

Lensless imaging offers a lightweight, compact alternative to traditional lens-based systems, ideal for exploration in space-constrained environments. However, the absence of a foc…

eess.IV2022

Shadow-Oriented Tracking Method for Multi-Target Tracking in Video-SAR

Xiaochuan Ni, Xiaoling Zhang, Xu Zhan +4

This work focuses on multi-target tracking in Video synthetic aperture radar. Specifically, we refer to tracking based on targets' shadows. Current methods have limited accuracy as…

eess.SP2022

A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging

Yu Ren, Xiaoling Zhang, Xu Zhan +3

Deep learning (DL)-based tomographic SAR imaging algorithms are gradually being studied. Typically, they use an unfolding network to mimic the iterative calculation of the classica…

eess.IV2022

Near-filed SAR Image Restoration with Deep Learning Inverse Technique: A Preliminary Study

Xu Zhan, Xiaoling Zhang, Wensi Zhang +3

Benefiting from a relatively larger aperture's angle, and in combination with a wide transmitting bandwidth, near-field synthetic aperture radar (SAR) provides a high-resolution im…

eess.SP2022

Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework

Xu Zhan, Xiaoling Zhang, Mou Wang +3

This work focuses on 3D Radar imaging inverse problems. Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the…