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cs.CV2026

A Deep Learning Iterative Framework for Sentinel-1 Stripmap Enhancement Based on Azimuth Doppler Decomposition

Juan Francisco Amieva, Christian Ayala, Roberto Del Prete +1

Synthetic Aperture Radar (SAR) imagery enables all-weather, day-and-night Earth observation; however, it remains difficult to interpret due to speckle noise and other intrinsic ima…

cs.CV2026

Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI

Parampuneet Kaur Thind, Vaibhav Katturu, Giacomo Zema +1

Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, including neural architecture sea…

cs.CV2025

Supervised and self-supervised land-cover segmentation & classification of the Biesbosch wetlands

Eva Gmelich Meijling, Roberto Del Prete, Arnoud Visser

Accurate wetland land-cover classification is essential for environmental monitoring, biodiversity assessment, and sustainable ecosystem management. However, the scarcity of annota…

cs.CV2024

Enhancing Maritime Situational Awareness through End-to-End Onboard Raw Data Analysis

Roberto Del Prete, Manuel Salvoldi, Domenico Barretta +5

Satellite-based onboard data processing is crucial for time-sensitive applications requiring timely and efficient rapid response. Advances in edge artificial intelligence are shift…

cs.CV2024

Unlocking the Use of Raw Multispectral Earth Observation Imagery for Onboard Artificial Intelligence

Gabriele Meoni, Roberto Del Prete, Federico Serva +3

Nowadays, there is growing interest in applying Artificial Intelligence (AI) on board Earth Observation (EO) satellites for time-critical applications, such as natural disaster res…