Aim: The main objective of the study is to recognize the license plate recognition system using Novel Convolution Neural Network(CNN) in comparison with Adaboost algorithm for the TRAIN dataset. Materials and Methods: Recognition of license plate is recognized using Novel Convolution Neural Network algorithm (N=20) and Adaboost (N=20).Convolution Neural Network algorithm is a supervised machine learning,Deep learning recognition algorithm, it is basically used for image classification and recognition because of its high accuracy. Adaboost algorithm are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. TRAIN dataset is used for recognition of license plate. Results: The accuracy of license plate recognition using the Novel Convolution Neural Network algorithm is 95.39% and Adaboost algorithm is 93.35%. There is a significant difference between Convolution Neural Network algorithm and Adaboost algorithm. Conclusion: Novel Convolution Neural Network algorithm seems to be more accurate than the Adaboost algorithm in recognition of license plate.