Graduate Research Assistant University of Connecticut Storrs Mansfield, Connecticut, United States
This study proposes an automated assessment of unhealthy tree crowns using deep learning convolutional neural networks and remote sensing. The method aims to accurately detect tree crown health status, offering increased efficiency, reduced costs, and improved accuracy compared to traditional manual methods.
Learning Objectives:
Upon completion, the participant will be able to identify the importance of remote sensing and deep learning techniques in forestry.
Upon completion, the participant will be able to define the convolutional neural networks and how they work.
