Fig. 1
From: Optimizing deep learning models for on-orbit deployment through neural architecture search
Block diagram of the proposed hardware-aware framework, which jointly optimizes task-specific performance metrics and device-specific latency. The graphical representation illustrates the AI-enabled Earth Observation (EO) data handling pipeline. In contrast to traditional processing chains-typically constrained by line-of-sight downlink windows of 8–12 min per orbit-the integration of onboard AI significantly reduces data volume by up to 85%, and decreases latency from hours to minutes.
