An Efficient Classification for Light Motor Vehicles using CatBoost Algorithm

Abstract

This paper proclaims the application of light motor vehicles (LMV) classification employing the unique algorithm named CatBoost (CB) algorithm to boost the accuracy in vehicle classification concerning features of colors and shapes. Normally, the classification grounded on non-identical parameters including label features, various classes, peculiar structures, features tobe extracted, segmented portrayal and connotation classification is greatly protested to incorporate in machine learning model. In this circumstance, the CatBoost algorithm has been utilized to gain high performance in LMV classification from the huge surveillance dataset. The empirical outcome accuracy is gained in LMV classification with high grade of resolution images.