engleski

Convolutional Neural Networks for Croatian Traffic Signs Recognition

We present an approach to recognition of Croatian traffic signs based on convolutional neural networks (CNNs). A library for quick prototyping of CNNs is first developed. An architecture similar to LeNet-5 is then created and tested on the MNIST dataset of handwritten digits where comparable results were obtained. We analyze the FER-MASTIF TS2010 dataset and propose a CNN architecture for traffic sign recognition. The presented experiments confirm the feasibility of CNNs for the defined task and suggest improvements to be made in order to improve recognition of Croatian traffic signs.

Convolutional networks, traffic sign recognition

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