Birdy: A Bird Detection System using CNN and Transfer Learning

Abstract

Identification of bird species is an important part of efforts to monitor and protect biodiversity. The routine process of brand identification is often labor-intensive and time-consuming. In this project, we use the power of deep learning, specifically convolutional neural networks (CNN) and Transfer Learning, to recognize bird species from image data. Transformational learning allows us to build advanced learning models that achieve high accuracy with little data. Our method is based on collecting large numbers of bird images and can identify many bird species. The findings not only improve the effectiveness of bird species research, but also help better understand bird ecosystems and promote conservation. In-depth research on bird species CNN Change study Biodiversity monitoring Species Identification Sustainable conservation