  Precise vertex reconstruction is essential for large liquid scintillator
detectors. A novel method based on machine learning has been successfully
developed to reconstruct the event vertex in JUNO previously. In this paper,
the performance of machine learning based vertex reconstruction is further
improved by optimizing the input images of the neural networks. By separating
the information of different types of PMTs as well as adding the information of
the second hit of PMTs, the vertex resolution is improved by about 9.4 % at 1
MeV and 9.8 % at 11 MeV, respectively.
