Per-plume tuned background estimators, especially K-Nearest Segments, substantially raise neural network confidence for gas plume identification on 640 simulated LWIR images, but the evaluation uses oracle hyperparameters and reports confidence rather than classification accuracy.
Detection algorithms for hyperspectral imaging applications,
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Improved Background Estimation for Gas Plume Identification in Hyperspectral Images
Per-plume tuned background estimators, especially K-Nearest Segments, substantially raise neural network confidence for gas plume identification on 640 simulated LWIR images, but the evaluation uses oracle hyperparameters and reports confidence rather than classification accuracy.