Machine Learning for Plant Disease Incidence and Severity Measurements from Leaf Images. - Ernest Mwebaze; Godliver Owomugisha (ICMLA, 2016)

Early detection of plant diseases using spectral data. - Godliver Owomugisha; Ephraim Nuwamanya; John A. Quinn; Michael Biehl; Ernest Mwebaze (APPIS, 2020)

A low-cost 3-D printed smartphone add-on spectrometer for diagnosis of crop diseases in field. - Godliver Owomugisha; Pius K. B. Mugagga; Friedrich Melchert; Ernest Mwebaze; John A. Quinn; Michael Biehl (COMPASS, 2020)

Matrix Relevance Learning From Spectral Data for Diagnosing Cassava Diseases. - Godliver Owomugisha; Friedrich Melchert; Ernest Mwebaze; John A. Quinn; Michael Biehl (IEEE Access, 2021)

A Light Spectrometer Device for Crop Disease Monitoring. - Joshua Jeremy Dhikusooka; Ephraim Nuwamanya; Estefania Talavera Martínez; Godliver Owomugisha (Tiny Papers @ ICLR, 2023)

A field-based recommender system for crop disease detection using machine learning. - Jonathan Omara; Estefanía Talavera; Daniel Otim; Dan Turcza; Emmanuel Ofumbi; Godliver Owomugisha (Frontiers Artif. Intell., 2023)

Deep Gaussian convolutional neural network model in classification of cassava diseases using spectral data. - Emmanuel Ahishakiye; Waweru Mwangi; Petronilla Muriithi; Fredrick Kanobe; Godliver Owomugisha; Danison Taremwa; Lenard Nkalubo (J. Supercomput., 2024)