Detection of Expiration Dates in Product Images Using YOLO - Andreotti, Lucas; Fraga, Lucas M.; Barros, Rodrigo C.; Kupssinskü, Lucas S. (Anais da Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região Sul (ERAMIA-RS); 2025: Anais da I Escola Regional de Aprendizado de Máquina e Inteligência Artificial da Região SulDO - 10.5753/eramiars.2025.16690, 2025)
Accurate identification of expiration dates on product packaging is essential to prevent the consumption of expired goods, reduce waste, and improve inventory management. This study proposes a YOLO-based neural network model for automatic detection of expiration dates in product packaging images. A dataset containing 668 images of Brazilian product packages was created, annotated, and made publicly available for training and evaluation purposes. Our fine-tuned YOLO achieved a precision of 0.804 and an F1-score of 0.812, indicating promising results for expiration date detection.