A Deep Artificial Neural Network-Based Daphne Leaf Classification Study

Abstract

Today, machine learning methods make life easier in almost every field, from production to consumption, and increase the speed of technology in a dizzying way. By integrating smart systems into industrial production, less costly but more effective products are offered to humanity. Undoubtedly, machine learning techniques contribute to the industry mostly in the field of image processing. In this study, a model is proposed to classify the leaves of the daphne plant, which is used in many different fields from cosmetics to gastronomy, by using YOLOv8, the most current version of the deep artificial neural network-based YOLO algorithm, which is one of the technologies in the field of image processing. Thanks to the model trained using the originally prepared dataset in the study, real-time daphne leaf classification can be performed successfully. © 2024 Elsevier B.V., All rights reserved.