From: Hesham ElBakoury <helbakoury@gmail.com>
To: 5grm-satellite@ieee.org,
Dave Taht via Starlink <starlink@lists.bufferbloat.net>
Subject: [Starlink] DeepSpace: Super Resolution Powered Efficient and Reliable Satellite Image Data Acquistion | Proceedings of the ACM SIGCOMM 2025 Conference
Date: Wed, 8 Apr 2026 10:46:29 -0700 [thread overview]
Message-ID: <CAFvDQ9o6UEZTtp-ZP1M61yNRO7Rm6chnNc9HuVAZ46935fLA3g@mail.gmail.com> (raw)
The authors of this sigcomm 2025 paper propose "DeepSpace, a new deep
learning-based super-resolution approach that compresses satellite imagery
by over two orders of magnitude, while preserving image quality using a
tailored mixture of experts (MoE) super-resolution framework. DeepSpace
reduces the network bandwidth requirements for space-Earth transfer, and
can compress images for cloud storage."
https://dl.acm.org/doi/10.1145/3718958.3750523
Hesham
reply other threads:[~2026-04-08 17:46 UTC|newest]
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