Browsing College of Engineering, Design, Art and Technology (CEDAT) by Subject "Vector Machines"
Now showing items 1-1 of 1
-
Comparison between Support Vector Machine and Random Forest Models in Estimating Tea Yields at Mwera Tea Farm using Sentinel and Landsat 8 Imagery.
(2021-12)Tea is the second-largest export cash crop of Uganda making tea a very important crop since it generates a lot of income for the government and the local people through its revenue generated from the export and selling ...