Automated Bird Classification using Deep Learning

Authors

Presenter(s)

Kasturi Avinash Jamale

Comments

Presentation: 3:00-4:15, Kennedy Union Ballroom

Files

Description

In this work, we introduce a novel approach to bird classification using deep learning methods. Leveraging YouTube videos, we collect annotated data for training a model capable of accurately identifying bird species. Our model is designed to handle various environmental factors and achieves high classification accuracy across diverse bird species. This work contributes to advancing automated bird classification techniques, offering valuable applications in ecological monitoring and conservation efforts.

Publication Date

4-17-2024

Project Designation

Graduate Research

Primary Advisor

Van Tam Nguyen

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium, College of Arts and Sciences

Recommended Citation

"Automated Bird Classification using Deep Learning" (2024). Stander Symposium Projects. 3555.
https://ecommons.udayton.edu/stander_posters/3555