Automated Detection of Ancient Indonesian Coins for Historical Numismatic Investigations - Rosalina, Rosalina (Universitas Medan Area, 2024)
This study focuses on cultural heritage preservation, employing the YOLOv8 model for detecting and classifying ancient Indonesian coins. Motivated by challenges in accurately identifying coins with diverse physical conditions, YOLOv8, introduced in January 2023, presents a groundbreaking advancement in computer vision. Meticulous testing on a curated dataset demonstrates the model's capacity to recognize unique features across various coin variations, marking a substantial stride in cultural heritage preservation. Contributing significantly to computer vision and cultural heritage studies, the research emphasizes key metrics in model evaluation—accuracy, recall, and precision. The rigorous assessment underscores the YOLOv8 system's efficiency and reliability in classifying ancient Indonesian coins, with experimentation yielding a commendable 91% accuracy. Beyond technical contributions, the study extends understanding of YOLOv8's capabilities, paving new avenues for object recognition in cultural preservation. This research serves as a milestone, advancing the integration of cutting-edge technology to safeguard and comprehend the rich cultural heritage embodied in ancient Indonesian coins.