Enhancing Lower Primary Students Engagement Through Object Detection in Cartoon Images

This paper presents an approach to object detection in cartoon images. This method is a critical component of a newly developed educational platform aimed at enhancing mother tongue language usage among Primary 1 and Primary 2 students. The platform's visual engine incorporates image analytics of cartoon imagery to support language learning. While most existing object detection models are optimized for real-world images, our work addresses the underexplored area of cartoon image analysis. By fine-tuning pre-existing models, our method demonstrates performance improvements in detecting objects within cartoon images. This research contributes to the broader goal of integrating visual learning tools into early childhood education, with the goal of fostering improved language skills through engaging and interactive content.