16 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…
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…
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…