  This paper presents a method for detection and recognition of traffic signs
based on information extracted from an event camera. The solution used a
FireNet deep convolutional neural network to reconstruct events into greyscale
frames. Two YOLOv4 network models were trained, one based on greyscale images
and the other on colour images. The best result was achieved for the model
trained on the basis of greyscale images, achieving an efficiency of 87.03%.
