mCROPS team, AI Research labs
Automated Diagnosis project takes shape with Spectrometry.
Author: Mutembesa Daniel
The automated diagnosis sub-project of mCROPS takes shape with Spectrometry and the newest release of server deployable classifiers for Cassava Mosaic Disease, Cassava Brwon Streak Disease, Cassava Bacterial Blight and Cassava Green Mite.
The sub-project is led by Ms. Godliver Owomugisha who is pursuing her doctoral research in developing and using low-cost spectrometry for non-intrusive diagnosis of cassava plant materials is research work that extends the gains made in automated diagnosis using image processing over diseased leaf images by Dr. Ernest Mwebaze.
The doctoral research is being conducted a sandwich programme between University of Groningen and Makerere University under the advisorship of Dr. Ernest Mwebaze and Prof.Michael Beihl.
The Automated diagnosis sub-project is also experimenting with various machine learning and classification techniques to build classification algorithms that are to deployed over the Adhoc Surveillance Map to be able to facilitate a dynamic heat map that changes to reporting of real-time surveillance data.
authored by: Mutembesa Daniel
Lead Researcher & Project Head | Adhoc Surveillance Project
a sub-project of mCROPS | www.mcrops.org