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arXiv AI By Luca Marini, Maggie Chen, Hala Lamdouar, Laura Mart\'inez-Ferrer, Dr C. P. Bridges, Giacomo Acciarini

Methane Detection On Board Satellites from Unorthorectified Imagery

Read the original on arXiv AI →

The paper introduces UnorthoDOS, a dataset and machine‑learning approach that enables methane plume detection directly on unorthorectified hyperspectral satellite imagery. Using U‑Net models trained on this data, the authors achieve performance close to models trained on orthorectified images (IoU 16.91% vs. 18.47%) and far surpass the traditional matched‑filter baseline (IoU 4.76%). They also demonstrate that FP16 compression can reduce model size by half with negligible loss in output accuracy, making onboard deployment feasible.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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