Engineering Commons^™

Classification Of Vegetation In Aerial Imagery Via Neural Network, Gevand Balayan

UNLV Theses, Dissertations, Professional Papers, and Capstones

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 …

Developing Silent Unmanned Aerial Vehicles, Glen Wright

Research on Capitol Hill

The optimization of a drone propeller’s acoustic signature can play an important role in the Department of Defense, observation of nature, commercial operations, and marine propulsion.

The aim of this research is to optimize the acoustic signature of propellers by isolating and modifying specific propeller characteristics. Propeller variations being researched in this project include:

• Leading-edge serrations: break up incoming fluid and evenly disperse it along airfoil
• Trailing-edge serrations: minimize vortex occurrences along the trailing edge of airfoil
• Airfoil ribs: force fluid through tangential channels along airfoil
• Winglets: disrupt turbulence and vortices at the tips of the propeller

Successful drone propeller …