Award Date

May 2019

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Evangelo Yfantis

Second Committee Member

Hal Berghel

Third Committee Member

John Minor

Fourth Committee Member

John Wang

Number of Pages

49

Abstract

This thesis focuses on the task of trying to find a Neural Network that is best suited for identifying vegetation from aerial imagery. The goal is to find a way to quickly classify items in an image as highly likely to be vegetation(trees, grass, bushes and shrubs) and then interpolate that data and use it to mark sections of an image as vegetation. This has practical applications as well. The main motivation of this work came from the effort that our town takes in conserving water. By creating an AI that can easily recognize plants, we can better monitor the impact they make on our water resources.

Keywords

Aerial; Classification; Imagery; Network; Neural; Vegatation

Disciplines

Artificial Intelligence and Robotics | Computer Engineering | Computer Sciences

Language

English


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