Master of Science in Computer Science
First Committee Member
Second Committee Member
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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.
Aerial; Classification; Imagery; Network; Neural; Vegatation
Artificial Intelligence and Robotics | Computer Engineering | Computer Sciences
University of Nevada, Las Vegas
Balayan, Gevand, "Classification of Vegetation in Aerial Imagery via Neural Network" (2019). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3568.
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