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Deep Learning Meets GPR: Exploring Transformer Models for Precision Soil Depth Prediction
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DOI：10.1016/j.envsoft.2026.107075.png)
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Abstract
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• Integrated GPR data with Transformer model to improve soil depth prediction accuracy. • Transformer outperformed all other algorithms across datasets of varying sizes. • Transformer eliminates the need for time-consuming variable selection processes. • GPR predictions revealed footslope soil depth reductions missed by auger method.
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