5 papers
Raw Imagery Impacting Your AI: Should You Care?
Adrien Dorise, Marjorie Bellizzi, Stéphane May
Onboard AI is gaining interest for space applications such as vessel, wildfire, and cloud detection, where real-time processing can improve mission reactivity and reduce downlink n…
Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction
Thomas Goudemant, Benjamin Francesconi, Marjorie Bellizzi +1
Rapid assessment of building damage after natural disasters is essential to support emergency response. Earth Observation satellites can acquire relevant imagery shortly after an e…
TriCCOT: Tri-part Convolutional Conformal Transformer for Onboard Space Object Detection
Adrien Dorise, Marjorie Bellizzi, Julia Cohen +1
Onboard object detection in Earth observation is constrained by limited computational resources and the absence of fully corrected imagery. While convolutional detectors are hardwa…
Rethinking Satellite Image Restoration for Onboard AI: A Lightweight Learning-Based Approach
Adrien Dorise, Marjorie Bellizzi, Omar Hlimi
Satellite image restoration aims to improve image quality by compensating for degradations (e.g., noise and blur) introduced by the imaging system and acquisition conditions. As a…
Explaining raw data complexity to improve satellite onboard processing
Adrien Dorise, Marjorie Bellizzi, Adrien Girard +2
With increasing processing power, deploying AI models for remote sensing directly onboard satellites is becoming feasible. However, new constraints arise, mainly when using raw, un…