Vehicle Recognition using Multi-Layer Perceptron and SMOTE Technique

Vehicle recognition is a significant problem to address. Primarily because of the different shapes of vehicles. It is hard for computer vision to achieve this goal. Our paper is intended to identify vehicles using a multi-layer perceptron (MLP) algorithm. Dataset used in this research is obtained from the Turing Institute, Glasgow, Scotland, present on the UCI machine learning repository website. This research consists of two stages. In the first stage, pre-processing is done in which SMOTE filter is applied to resamples a dataset. The Multi-layer perceptron (MLP) algorithm is applied in the second stage for classification. It is pointed out that the proposed model obtained the highest classification accuracy of 86.02 %. Performance of MLP is evaluated on the accuracy, precision, F1-Score, and MCC.