College of Engineering Unit:
Electrical Engineering and Computer Science
Project Team Member(s):
None Listed
Physical Location at Expo:
Community Plaza
Project ID:
CS.057
Project Description:
We've created an FOSS QGIS plugin that can automate .TIF image importing, execution of maximum likelihood algorithm, and allow of external inputs from the user for a multi-band image when given treatment areas using python. The purpose of this project is to identity the invasive plant species- Reed Canary on a plot of land. The AI pipeline can reduce work loads of field operatives onsite and run various machine learning algorithms to identify the location of the grass.