68 citations · 730 across the 54 of their papers we have counts for
55 papers
Multitask Learning for Earth Observation Data Classification with Hybrid Quantum Network
Fan Fan, Yilei Shi, Tobias Guggemos +1
Quantum machine learning (QML) has gained increasing attention as a potential solution to address the challenges of computation requirements in the future. Earth observation (EO) h…
Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning
Fan Fan, Yilei Shi, Mihai Datcu +5
Machine Learning (ML) has been widely applied across numerous domains due to its ability to automatically identify informative patterns from data for various tasks. The availabilit…
Reconstructing Building Height from Spaceborne TomoSAR Point Clouds Using a Dual-Topology Network
Zhaiyu Chen, Yuanyuan Wang, Yilei Shi +1
Reliable building height estimation is essential for various urban applications. Spaceborne SAR tomography (TomoSAR) provides weather-independent, side-looking observations that ca…
Physically consistent and uncertainty-aware learning of spatiotemporal dynamics
Qingsong Xu, Jonathan L Bamber, Nils Thuerey +5
Accurate long-term forecasting of spatiotemporal dynamics remains a fundamental challenge across scientific and engineering domains. Existing machine learning methods often neglect…
High-Order Progressive Trajectory Matching for Medical Image Dataset Distillation
Le Dong, Jinghao Bian, Jingyang Hou +5
Medical image analysis faces significant challenges in data sharing due to privacy regulations and complex institutional protocols. Dataset distillation offers a solution to addres…
Multimodal Large Language Models for Medical Report Generation via Customized Prompt Tuning
Chunlei Li, Jingyang Hou, Yilei Shi +3
Medical report generation from imaging data remains a challenging task in clinical practice. While large language models (LLMs) show great promise in addressing this challenge, the…
GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models
Xiao Xiang Zhu, Sining Chen, Fahong Zhang +2
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models.…
Enhancing Monocular Height Estimation via Weak Supervision from Imperfect Labels
Sining Chen, Yilei Shi, Xiao Xiang Zhu
Monocular height estimation provides an efficient and cost-effective solution for three-dimensional perception in remote sensing. However, training deep neural networks for this ta…
Global Collinearity-aware Polygonizer for Polygonal Building Mapping in Remote Sensing
Fahong Zhang, Yilei Shi, Xiao Xiang Zhu
This paper addresses the challenge of mapping polygonal buildings from remote sensing images and introduces a novel algorithm, the Global Collinearity-aware Polygonizer (GCP). GCP,…
CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention
Yaxiong Chen, Minghong Wei, Zixuan Zheng +5
Referring medical image segmentation targets delineating lesions indicated by textual descriptions. Aligning visual and textual cues is challenging due to their distinct data prope…
UniCrossAdapter: Multimodal Adaptation of CLIP for Radiology Report Generation
Yaxiong Chen, Chuang Du, Chunlei Li +5
Automated radiology report generation aims to expedite the tedious and error-prone reporting process for radiologists. While recent works have made progress, learning to align medi…
One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks
Yaxiong Chen, Junjian Hu, Chunlei Li +6
Video object segmentation is crucial for the efficient analysis of complex medical video data, yet it faces significant challenges in data availability and annotation. We introduce…
Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Zixuan Zheng, Yilei Shi, Chunlei Li +3
Few-shot video object segmentation aims to reduce annotation costs; however, existing methods still require abundant dense frame annotations for training, which are scarce in the m…
Striving for Simplicity: Simple Yet Effective Prior-Aware Pseudo-Labeling for Semi-Supervised Ultrasound Image Segmentation
Yaxiong Chen, Yujie Wang, Zixuan Zheng +5
Medical ultrasound imaging is ubiquitous, but manual analysis struggles to keep pace. Automated segmentation can help but requires large labeled datasets, which are scarce. Semi-su…
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
Chunlei Li, Yilei Shi, Jingliang Hu +2
Unsupervised anomaly detection using deep learning has garnered significant research attention due to its broad applicability, particularly in medical imaging where labeled anomalo…
Q-PART: Quasi-Periodic Adaptive Regression with Test-time Training for Pediatric Left Ventricular Ejection Fraction Regression
Jie Liu, Tiexin Qin, Hui Liu +5
In this work, we address the challenge of adaptive pediatric Left Ventricular Ejection Fraction (LVEF) assessment. While Test-time Training (TTT) approaches show promise for this t…
Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation
Shan Zhao, Zhaiyu Chen, Zhitong Xiong +3
Earth Observation (EO) data analysis has been significantly revolutionized by deep learning (DL), with applications typically limited to grid-like data structures. Graph Neural Net…
Physics-embedded Fourier Neural Network for Partial Differential Equations
Qingsong Xu, Nils Thuerey, Yilei Shi +3
We consider solving complex spatiotemporal dynamical systems governed by partial differential equations (PDEs) using frequency domain-based discrete learning approaches, such as Fo…
GlobalBuildingMap -- Unveiling the Mystery of Global Buildings
Xiao Xiang Zhu, Qingyu Li, Yilei Shi +3
Understanding how buildings are distributed globally is crucial to revealing the human footprint on our home planet. This built environment affects local climate, land surface albe…
On the Foundations of Earth and Climate Foundation Models
Xiao Xiang Zhu, Zhitong Xiong, Yi Wang +7
Foundation models have enormous potential in advancing Earth and climate sciences, however, current approaches may not be optimal as they focus on a few basic features of a desirab…
Large-scale flood modeling and forecasting with FloodCast
Qingsong Xu, Yilei Shi, Jonathan Bamber +2
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to a…
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu, Yilei Shi, Jonathan Bamber +3
Accurate hydrological understanding and water cycle prediction are crucial for addressing scientific and societal challenges associated with the management of water resources, part…
HTC-DC Net: Monocular Height Estimation from Single Remote Sensing Images
Sining Chen, Yilei Shi, Zhitong Xiong +1
3D geo-information is of great significance for understanding the living environment; however, 3D perception from remote sensing data, especially on a large scale, is restricted. T…
HyperLISTA-ABT: An Ultra-light Unfolded Network for Accurate Multi-component Differential Tomographic SAR Inversion
Kun Qian, Yuanyuan Wang, Peter Jung +2
Deep neural networks based on unrolled iterative algorithms have achieved remarkable success in sparse reconstruction applications, such as synthetic aperture radar (SAR) tomograph…