3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2026
Flow matching for Sentinel-2 super-resolution: implementation, application, and implications
Dakota Hester, Vitor S. Martins, Lucas B. Ferreira +2
Developing robust techniques for super-resolution of satellite imagery involves navigating commonly observed trade-offs between spectral fidelity and perceptual quality. In this wo…
cs.CV2025
Learning with less: label-efficient land cover classification at very high spatial resolution using self-supervised deep learning
Dakota Hester, Vitor S. Martins, Lucas B. Ferreira +1
Deep learning semantic segmentation methods have shown promising performance for very high 1-m resolution land cover classification, but the challenge of collecting large volumes o…
cs.CV2023★ 3 cited
A Self-Supervised Approach to Land Cover Segmentation
Charles Moore, Dakota Hester
Land use/land cover change (LULC) maps are integral resources in earth science and agricultural research. Due to the nature of such maps, the creation of LULC maps is often constra…