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Detection of Hijaiyah Letters Handwritten in Early Childhood Using Yolov8

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YOLOv8 achieved 96.08% accuracy in detecting handwritten hijaiyah letters, validating its reliability for educational purposes.
The model showed high precision and recall rates, indicating its effectiveness in recognizing various writing styles among children.
A dataset of 3,780 images was meticulously curated, ensuring model robustness and reliability across different handwriting variations.
Preprocessing techniques including resizing and data augmentation enhanced the training data quality, contributing to the model's successful implementation.

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Research demonstrates YOLOv8's 96.08% accuracy in detecting hijaiyah letters, highlighting its role in literacy enhancement.

Mustagfiroh et al. (2025) studied this question.

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