Multi-modal crop yield prediction — Cameroon
Six deep learning architectures over three nested datasets — satellite, climate, socio-economic — for maize, cassava and cocoa.
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Reconstructing incomplete agricultural production series
Ensemble statistical reconstruction under hard agronomic constraints, to fill and backfill maize and onion production series for the Centre region.
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The impact of socio-economic data on deep learning crop yield prediction in Cameroon
In preparation. A controlled nested-dataset experiment isolating the marginal contribution of satellite, climate and socio-economic data across six deep learning architectures.
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Deep learning for crop monitoring: a systematic review
Mbalkam et al. (2025). A PRISMA systematic review of 87 studies across 10 deep learning architecture families applied to crop monitoring.