Search

In this study, the aim is to give general information about machine learning and Local Binary Pattern (LBP) and to classify sainfoin (Onobrychis) plant fruits grown in Türkiye with machine learning in the light of this information. A database was created using a total of 448 fruit images of 4 different Sainfoin (Onobrychis) species. These species are O. cappadocica, O. argyrea, O. hypargyrea and O. tournefortii, respectively. Machine learning methods were used to classify sainfoin (Onobrychis) fruit varieties. These methods were classified by four different methods, namely Support Vector Machine Method, Naive Bayes Algorithm Method, Decision Trees Method and K-Nearest Neighbor Method. The performances of these four different methods were compared and it was determined that the most suitable model was the Support Vector Machine Method with a 99.6% correct classification success rate. [ABSTRACT FROM AUTHOR]