Modeling of the facial recognizing distance by Machine Learning techniques

Abstract: The project dealt with the elaboration of a mathematical algorithm for determination of the facial recognizing distance in urban streets. The algorithm was implemented in an app to find the most secure paths to move in towns by night. Several Machine learning techniques were used to approximate the data of facial recognizing provided by the company IMESAPI, determining the most appropriate in terms of accuracy.
The prediction algorithm was delivered to IMESAPI.

Researchers:  Tomás Chacón Rebollo, Emilio Carrizosa, Sándra Benítez Peña, Rafael Blanquero.

Partner: IMESAPI

iMAT research lines:     ⊕ RL1. Modeling of Energy Systems.      RL4: Modeling in Transport & Logistics     ⊕ RL6: The Mathematics of Data Science