  A neural network technique is used to discriminate between quark and gluon
jets produced in the qg->q+photon and q q->g+photon processes at the LHC.
Considering the network as a trigger and using the PYTHIA event generator and
the full event fast simulation package for the CMS detector CMSJET we obtain
signal-to-background ratios.
