Alessio Pardini

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

On-board processing is emerging as a key enabler for Earth observation (EO) missions, reducing downlink requirements and supporting more autonomous, event-driven operations. Deep convolutional neural networks (CNNs) deliver state-of-the-art performance on many EO tasks, but their memory footprint and computational dema...