Plume Segmentation from MethaneSAT with Cross-Sensor Transfer Learning and Physics-Informed Postprocessing
cs.CV, physics.ao-ph
Submitted: 2026-05-22
Updated: 2026-10-10
Terminology
Sources
- Towards Operational Automated Greenhouse Gas Plume Detection and Delineation
- U-Net: Convolutional Networks for Biomedical Image Segmentation
- AI for operational methane emitter monitoring from space
- Unlocking the Potential: Multi-task Deep Learning for Spaceborne Quantitative Monitoring of Fugitive Methane Plumes
- AttMetNet: Attention-Enhanced Deep Neural Network for Methane Plume Detection in Sentinel-2 Satellite Imagery
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- Global monitoring of methane point sources using deep learning on hyperspectral radiance measurements from EMIT
- Deep Learning using Rectified Linear Units (ReLU)
- Decoupled Weight Decay Regularization
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