Exploring machine learning algorithms for mapping crop types in a heterogeneous agriculture landscape using Sentinel-2 data. A case study of Free State Province, South AfricaTheresa Taona Mazarire, George Chirima, Elhadi Adam et al.|South African Journal of Geomatics|2022Cited by 14
Identification of maize leaf diseases using red, green, blue-based images with convolutional neural network (CNN) and residual network (ResNet50) modelsBasani Lammy Nkuna, Adolph Nyamugama, George Chirima et al.|Smart Agricultural Technology|2025Cited by 6
Developing models to detect maize diseases using spectral vegetation indices derived from spectral signaturesBasani Lammy Nkuna, A. J. van der Walt, Solomon W. Newete et al.|The Egyptian Journal of Remote Sensing and Space Science|2024Cited by 5
Predicting smallholder maize yield using sentinel-2-derived phenological metricsWonga Masiza, Hamisai Hamandawana, Basani Lammy Nkuna et al.|Smart Agricultural Technology|2026Cited by 4
Unraveling the Relationship between Soil Nutrients and Maize Leaf Disease Occurrences in Mopani District Municipality, Limpopo Province, South AfricaBasani Lammy Nkuna, Adolph Nyamugama, George Chirima et al.|Agronomy|2024Cited by 1