From the 1 of 11 linked papers with an AI index.
11 papers
Geometry-Calibrated Closed-Form Shrinkage for SAR Despeckling
Xuran Hu, Mingzhe Zhu, Djordje Stanković +4
Synthetic aperture radar (SAR) despeckling is an inverse-recovery problem in which multiplicative non-Gaussian noise must be suppressed without erasing scattering structures. We re…
Uncertainty Quantification for EO Regression Tasks: Building Height, Tree Canopy Height and Above-ground Biomass Estimation
Ritu Yadav, Andrea Nascetti, Yifang Ban
The paper proposes two deep learning methods to estimate per‑pixel uncertainty for Earth observation regression tasks such as building height, canopy height, and above‑ground bioma…
Uncertainty-Aware Cross-Modal Remote Sensing Image-Text Retrieval via Evidential Learning
Zhuoyue Wang, Xueqian Wang, Gang Li +3
In cross-modal remote sensing image-text retrieval (CMRSITR), test-time remote sensing (RS) images and textual descriptions may deviate from well-curated benchmark conditions due t…
SAR Despeckling via Region-Aware Sparse Representation and Statistical Noise Approximation
Xuran Hu, Mingzhe Zhu, Djordje StankoviÄ +3
Synthetic Aperture Radar (SAR) imagery are widely utilized in remote sensing due to their all-weather, all-day imaging capabilities. However, SAR images are highly susceptible to n…
Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data
Ali Shibli, Andrea Nascetti, Yifang Ban
Wildfire burned-area mapping is essential for damage assessment, emissions modeling, and understanding fire-climate interactions across diverse ecological regions. Recent geospatia…
Noise2Map: End-to-End Diffusion Model for Semantic Segmentation and Change Detection
Ali Shibli, Andrea Nascetti, Yifang Ban
Semantic segmentation and change detection are two fundamental challenges in remote sensing, requiring models to capture either spatial semantics or temporal differences from satel…