A robust test for isotropy in 2D lattice data is introduced using robust variogram estimators and block permutation resampling to control significance levels under strong dependence and outliers.
Remote Sensing of Environment 8:127--150
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A comparative review with experiments identifying optimal preprocessing, models, and transfer strategies for large-scale pixel-wise crop mapping using Landsat 8 data across five sites.
CBAM-augmented EfficientNet-B3 with evidential deep learning classifies wildfire smoke severity into three levels on 16k satellite patches, reports 93.8% weighted accuracy, and decomposes epistemic and aleatoric uncertainty without Monte Carlo sampling.
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A robust nonparametric test for spatial isotropy in lattice data
A robust test for isotropy in 2D lattice data is introduced using robust variogram estimators and block permutation resampling to control significance levels under strong dependence and outliers.
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From Time-series Generation, Model Selection to Transfer Learning: A Comparative Review of Pixel-wise Approaches for Large-scale Crop Mapping
A comparative review with experiments identifying optimal preprocessing, models, and transfer strategies for large-scale pixel-wise crop mapping using Landsat 8 data across five sites.
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Uncertainty-Aware Wildfire Smoke Density Classification from Satellite Imagery via CBAM-Augmented EfficientNet with Evidential Deep Learning
CBAM-augmented EfficientNet-B3 with evidential deep learning classifies wildfire smoke severity into three levels on 16k satellite patches, reports 93.8% weighted accuracy, and decomposes epistemic and aleatoric uncertainty without Monte Carlo sampling.