Abstract
Although there are many datasets publicly available for specific domains, there are many possible applications of deep learning where no or limited data is available. Within this project, we analyzed the relationship between the amount of training-data and the accuracy of image classifiers. We used three different datasets with traffic signs images were used for training recent deep learning with different subsets sizes of the original datasets.