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 Sul, 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.