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UID:pretalx-foss4g-2025-WPLVJQ@talks.staging.osgeo.org
DTSTART;TZID=NZST:20251119T163000
DTEND;TZID=NZST:20251119T165500
DESCRIPTION:Leave-one-field-out tests on Malawian smallholder plots compare
  multiband/index linear regression\, XGBoost\, CNN-LSTM\, a frozen ViT and
  a ViT-LSTM on Sentinel-2 VT–R1 stacks. ViT-LSTM delivers the best accur
 acy (RMSE 0.022 t ha⁻¹) but runs 2.5 × slower than CNN-LSTM.
DTSTAMP:20260428T173446Z
LOCATION:WG802
SUMMARY:GeoAI Transformer–LSTM Boosts Maize-Yield Accuracy in Malawi’s 
 Smallholder Fields - Kondwani Munthali\, Mathews Jere
URL:https://talks.staging.osgeo.org/foss4g-2025/talk/WPLVJQ/
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