Author

Junghwan Park

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Preprint Aug 2026

ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink

The acquisition of multispectral imagery via small satellites (e.g., CubeSats) presents significant data downlink challenges due to high data volumes and restricted communication windows. While onboard image compression is critical to address this bottleneck, traditional methods often struggle to adapt to the nonlinear...

Woojin Cho, Junghwan Park, S. Sim et al. · 0 citations

Jul 2026

Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion

It is shown that a better name repairs part of the gap, while the remaining failures call for an address that the tested natural-language rephrasings do not provide, and the model improves over few-shot methods that instead inject visual prompts at inference.

Junhyuk Heo, Junghwan Park · arXiv.org · 0 citations

Preprint Aug 2026

Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation

This work proposes a "Summarize First, Download Later" paradigm that exploits recent advances in onboard edge computing and Vision-Language Models (VLMs) and substantially reduces bandwidth consumption while accelerating time-to-insight for time-sensitive missions.

Junghwan Park, S. Sim, Woojin Cho et al. · 0 citations