G. Di Palma

On-board efficiency: comparing compressed deep learning and classical models for Earth observation

A unified experimental framework is introduced that jointly evaluates compressed deep learning models and CML ensembles on two representative EO benchmarks and provides empirical guidance for selecting model families and compression strategies when designing future on-board EO systems.