Using machine learning techniques to calculate damage of vehicles involved in an accident

Abstract

Disclosed systems and methods incorporate machine learning to assess damage to vehicles. An example method includes: accessing image data representing one or more digital images of damage to a vehicle; selecting, using one or more processors, an applicable machine learning algorithm from a plurality of different trained machine learning algorithms, wherein the plurality of different machine learning algorithms are trained for respective different combinations of one or more of vehicle make, vehicle model, vehicle year, or area of damage; processing the image data, with the applicable machine learning algorithm using one or more processors, to determine assessed damage for the vehicle; accessing actual damage information for the vehicle; determining, using one or more processors, differences between the actual damage and the assessed damage; and iterating, using one or more processors, the applicable machine learning algorithm based on the differences to improve its damage assessment accuracy.