Machine Learning for electromagnetic showers reconstruction in emulsion cloud chambers

Traces of electromagnetic showers in the neutrino experiments may be considered as signals of dark matter particles. For example, SHiP experiment is going to use emulsion film detectors similar to the ones designed for OPERA experiment from dark matter search. The goal of this research is to develop an algorithm that can identify traces of electromagnetic showers in particle detectors, so it would be possible to analyse and compare various dark matter hypothesis. Both real data and signal simulation samples for this research come from OPERA experiment. Also we have used exploited algorithm for electromagnetic showers identification as a baseline. Although in this research we have used no hints about shower origin.