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TRAFFIC SIGN RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS / KELIO ŽENKLŲ ATPAŽINIMAS NAUDOJANT NEURONINĮ TINKLĄ
2018
Mokslas: Lietuvos Ateitis
Traffic sign recognition is an important method that improves the safety in the roads, and this system is an additional step to autonomous driving. Nowadays, to solve traffic sign recognition problem, convolutional neural networks (CNN) can be adopted for its high performance well proved for computer vision applications. This paper proposes histogram equalization preprocessing (HOG) and CNN with additional operations – batch normalization, dropout and data augmentation. Several CNN
doi:10.3846/mla.2018.6947
fatcat:3cqqr7bndbh37iiqsk3ysgekca