A Comparative Classification of Wheat Grains for Artificial Neural Network and Extreme Learning Machine

In this study, classification of two types of wheat grains into bread and durum was carried out. The species of wheat grains in this dataset are bread and durum and these species have equal samples in the dataset as 100 instances. Seven features, including width, height, area, perimeter, roundness, width and perimeter/area were extracted from each wheat grains. Classification was separately conducted by Artificial Neural Network (ANN) and Extreme Learning Machine (ELM) artificial intelligence techniques. Then the performances of models are compared each other. The accuracy of testing was calculated 97.89% and 96.79% for ANN and ELM, respectively.