A locality-aware embedding anomaly detector identifies label errors in global crop reference data; conservative cleaning raises WorldCereal crop-type macro-F1 in all five tested regions.
Title resolution pending
1 Pith paper cite this work, alongside 109 external citations. Polarity classification is still indexing.
1
Pith paper citing it
109
external citations · OpenAlex
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Embeddings based Anomaly Detection for Cleaning Global Crop Type Reference Datasets
A locality-aware embedding anomaly detector identifies label errors in global crop reference data; conservative cleaning raises WorldCereal crop-type macro-F1 in all five tested regions.