MAPL-EMIT, an end-to-end vision transformer, detects 79% of known hand-annotated EMIT methane plume complexes and twice as many plausible plumes as human analysts while supporting quantification and multi-plume handling.
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UNVERDICTED 2representative citing papers
MARS-S2L ML model detects methane plumes in multispectral satellite imagery at 78% recall with 8% false positives on unseen sites and has enabled verified permanent mitigation at six persistent emitters including a long-running super-emitter in Algeria.
citing papers explorer
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Global monitoring of methane point sources using deep learning on hyperspectral radiance measurements from EMIT
MAPL-EMIT, an end-to-end vision transformer, detects 79% of known hand-annotated EMIT methane plume complexes and twice as many plausible plumes as human analysts while supporting quantification and multi-plume handling.
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Artificial intelligence for methane detection: from continuous monitoring to verified mitigation
MARS-S2L ML model detects methane plumes in multispectral satellite imagery at 78% recall with 8% false positives on unseen sites and has enabled verified permanent mitigation at six persistent emitters including a long-running super-emitter in Algeria.