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SatUnreal: A High-Precision Synthetic Dataset for Satellite Stereo Matching via Unreal Engine
Han-Gyeol Kim, JaeWan Park, Junmin Park +1
3D reconstruction from satellite imagery is essential for large-scale topographic analysis, yet the lack of high-fidelity training datasets with accurate occlusion labels remains a…
Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation
Junghwan Park, Sangcheol Sim, Woojin Cho +1
Modern Earth observation (EO) satellites carry increasingly advanced sensors that produce vast volumes of high-resolution, multispectral data, yet downlink capacity remains a criti…
ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink
Woojin Cho, Junghwan Park, Sangcheol Sim +3
The acquisition of multispectral imagery via small satellites (e.g., CubeSats) presents significant data downlink challenges due to high data volumes and restricted communication w…
MANGO: A Global Single-Date Paired Dataset for Mangrove Segmentation
Junhyuk Heo, Beomkyu Choi, Hyunjin Shin +1
Mangroves are critical for climate-change mitigation, requiring reliable monitoring for effective conservation. While deep learning has emerged as a powerful tool for mangrove dete…