  The present paper shows a solution to the problem of automatic distress
detection, more precisely the detection of holes in paved roads. To do so, the
proposed solution uses a weightless neural network known as Wisard to decide
whether an image of a road has any kind of cracks. In addition, the proposed
architecture also shows how the use of transfer learning was able to improve
the overall accuracy of the decision system. As a verification step of the
research, an experiment was carried out using images from the streets at the
Federal University of Tocantins, Brazil. The architecture of the developed
solution presents a result of 85.71% accuracy in the dataset, proving to be
superior to approaches of the state-of-the-art.
