Vehicle pattern recognition in a novel way using KNN and compare prediction accuracy with CNN algorithm

The aim is to determine the vehicle pattern recognition of car models accurately using KNN and CNN algorithms. The Pattern recognition by CNN and KNN with sample size of 10 with 95% confidence level and G power of 80% for predicting accuracy percentage of vehicle pattern recognition of car model. The CNN calculation was done using the sigmoid function to predict the accuracy percentage. CNN has significantly better accuracy of 96.65% compared to KNN accuracy of 80.0%. CNN algorithm helps in estimating Vehicle pattern recognition with better accuracy percentage compared to KNN.