  Nowadays autonomous technologies are a very heavily explored area and
particularly computer vision as the main component of vehicle perception. The
quality of the whole vision system based on neural networks relies on the
dataset it was trained on. It is extremely difficult to find traffic sign
datasets from most of the counties of the world. Meaning autonomous vehicle
from the USA will not be able to drive though Lithuania recognizing all road
signs on the way. In this paper, we propose a solution on how to update model
using a small dataset from the country vehicle will be used in. It is important
to mention that is not panacea, rather small upgrade which can boost autonomous
car development in countries with limited data access. We achieved about 10
percent quality raise and expect even better results during future experiments.
