Abstract: A method and computing apparatus for determining comprehensive vehicle information using an intelligent Vehicle Identification Number (“VIN”) decoder process is described. The method and computing apparatus obtains OEM marketing data, OEM engineering data, parts catalog data, uses a machine learning algorithm to determine relational dependencies between the obtained OEM data and standard comprehensive vehicle configuration data to generate complete vehicle data using VIN.

Abstract: A method, non-transitory computer readable medium, and apparatus that improves automated damage appraisal includes analyzing one or more obtained images of property using a deep neural network with multiple hidden layers of units between an input and output and which has stored knowledge data encoded from one or more stored property damage images to identify the part of the vehicle that has sustained damage. Damage data on an extent of the damage in the identified part of the vehicle is determined using the deep neural network which has stored knowledge data encoded from one or more stored property damage images. The identified generic part of the vehicle is used to obtain a corresponding Part ID Code by using a parts dictionary. Part Qualifier information obtained using VIN information is then used in conjunction with the Part ID to obtain the OEM-specific part and then generate one or more repair lines for the repair estimate.