Bird Recognition Project Secured Cornell Admission

Charles' AI_Birder aims to provide birdwatchers, especially beginners, with a simple and convenient way to identify the birds they observe. It simplifies the identification process without relying on an internet connection, by uploading a photo of the bird to get information and identification results.

Student Testimonial

Charles crafted an intuitive interface using Flutter, supported by the powerful Firebase database for backend operations, and employed TensorFlow's deep learning algorithms to achieve a high accuracy rate of 79% for the AI engine. Without the need for an internet connection or complicated procedures, bird enthusiasts only need a single photo to quickly learn the name of the feathered friend before them.

More About This Project + Accolades

Admitted to Cornell University