An automated ML-plus-physics pipeline detects trace gas plumes in EMIT spectrometer data, flagging major events in real time and recovering at least 25% of plumes missed by prior human review.
Science Advances 9(46), eadh2391 (2023)
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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.
Proposes a generative-AI framework integrating smart metering, quantum-inspired optimization for gas distribution, billing, and carbon analytics in energy infrastructure.
citing papers explorer
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Fully Automatic Trace Gas Plume Detection
An automated ML-plus-physics pipeline detects trace gas plumes in EMIT spectrometer data, flagging major events in real time and recovering at least 25% of plumes missed by prior human review.
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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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A Unified Generative-AI Framework for Smart Energy Infrastructure: Intelligent Gas Distribution, Utility Billing, Carbon Analytics, and Quantum-Inspired Optimisation
Proposes a generative-AI framework integrating smart metering, quantum-inspired optimization for gas distribution, billing, and carbon analytics in energy infrastructure.