Development and Optimization of Classification Neural Networks for Disaster-Assessment Using Unmanned Aerial Vehicle Systems

Name

Maria Isabel Gonzalez Bocanegra, Georgia Southern UniversityFollow

Publication Date

5-16-2022

Major

Electrical and Computer Engineering (B.S.)

Document Type and Release Option

Thesis (open access)

Faculty Mentor

Dr. Rami J. Haddad

Abstract

This research focuses on increasing the classification accuracy of convolutional neural networks in an autonomous network of unmanned aerial vehicles for transportation disaster management. The autonomous network of UAVs will allow first responders to optimize their rescue plans by providing relevant information on inaccessible roads. The research seeks to explore different methods to optimize the architecture of convolutional networks for the multiclass classification of disaster-damaged roads.

Recommended Citation

Gonzalez Bocanegra, Maria Isabel, "Development and Optimization of Classification Neural Networks for Disaster-Assessment Using Unmanned Aerial Vehicle Systems" (2022). Honors College Theses. 776.
https://digitalcommons.georgiasouthern.edu/honors-theses/776