Project information

• Category: Machine learning
• Client: University of Kelaniya
• Project URL: project link

This project was focused on exploring the use of Tranfer learning to classify diseases in tea leaves.

In this project, an advanced application of YOLO (You Only Look Once) object detection technology has been harnessed to address a crucial educational concern: dyslexia detection in children's handwriting. By leveraging YOLO's exceptional ability to recognize and locate objects within images, the project focuses on the intricate task of identifying mirrored letters within words—a hallmark trait of dyslexia.

By analyzing the handwriting samples provided by children, the system accurately pinpoints instances of reversed letters, shedding light on potential signs of dyslexia. This technology-driven approach not only streamlines the diagnostic process but also offers a non-invasive and efficient method for educators, parents, and specialists to promptly identify dyslexia indicators in a child's written expression.