To evaluate the accuracy of the models, we use 3-folds
cross validation schema for all of the stages.
In the license plate area recognition stage, the model gets
99.0% of accuracy when we use 750 images for training and
243 images for testing.
In the letter area recognition stage, the model achieves
95.88% of accuracy when using 11,866 and 4,755 images for
training and testing, respectively.