collaborators

6 papers

eess.IV2026

MSTF-Net: A UAV-Oriented Multi-Spectral Video Segmentation Method via Modality-Robust, Scale-Adaptive, and Consistent Fusion

Chenwei Wang, Zhida Wang, Zelin Li +2

Multi-spectral video segmentation is essential for robust scene understanding in unmanned aerial vehicle (UAV) applications such as city planning, land use monitoring, traffic moni…

eess.IV2026

Recover Cell Tensor: Diffusion-Equivalent Tensor Completion for Fluorescence Microscopy Imaging

Chenwei Wang, Zhaoke Huang, Zelin Li +1

Fluorescence microscopy (FM) imaging is a fundamental technique for observing live cell division, one of the most essential processes in the cycle of life and death. Observing 3D l…

physics.bio-ph2025

CTransformer: Deep-transformer-based 3D cell membrane tracking with subcellular-resolved molecular quantification

Zelin Li, Guoye Guan, Xiu Xian +13

Deep learning segmentation and fluorescence imaging techniques allow the cellular morphology of living embryos to be constructed spatiotemporally. These development processes invol…

eess.IV2025

An Interpretable Two-Stage Feature Decomposition Method for Deep Learning-based SAR ATR

Chenwei Wang, Renjie Xu, Congwen Wu +5

Synthetic aperture radar automatic target recognition (SAR ATR) has seen significant performance improvements with deep learning. However, the black-box nature of deep SAR ATR intr…

eess.SP2025

CiUAV: A Multi-Task 3D Indoor Localization System for UAVs based on Channel State Information

Cunyi Yin, Chenwei Wang, Jing Chen +4

Accurate indoor positioning for unmanned aerial vehicles (UAVs) is critical for logistics, surveillance, and emergency response applications, particularly in GPS-denied environment…

eess.IV2025

Volume Tells: Dual Cycle-Consistent Diffusion for 3D Fluorescence Microscopy De-noising and Super-Resolution

Zelin Li, Chenwei Wang, Zhaoke Huang +4

3D fluorescence microscopy is essential for understanding fundamental life processes through long-term live-cell imaging. However, due to inherent issues in imaging principles, it…