  A proof-of-concept solution based on the machine learning techniques has been
implemented and tested within the MUonE experiment designed to search for New
Physics in the sector of anomalous magnetic moment of a muon. The results of
the DNN based algorithm are comparable to the classical reconstruction,
reducing enormously the execution time for the pattern recognition phase. The
present implementation meets the conditions of classical reconstruction,
providing an advantageous basis for further studies.
