Aim: To Enhance the Accuracy of Vehicle Based on Speed using Convolution Neural Networks in comparison to Support Vector Machine. Materials and Methods: Detection and Classification of Vehicles is a demanding concern. This study contains two groups i.e Novel Convolution Neural Networks over Support Vector Machine. Each group consists of a sample size of 10 and the study parameters include alpha value 0.05, beta value 0.2 and the power value 0.8. Results: The Novel Convolution Neural Networks is 85.50% more accurate than the support vector machine of 71.80% in Vehicle Detection. Conclusion: The CNN model is significantly better than the SVM in Analysis of Vehicle Detection. It can be also considered as a better option for vehicle detection. The significance value for performance and loss is 0.921 (p>0.05)