Method of universal automated verification of vehicle damage

1 . A computer-implemented method of generating a damage classification for a vehicle, comprising:

receiving a plurality of images of the vehicle wherein some of the images comprise image data of damage to the vehicle;

determining, using one or more classifiers that are specific to a plurality of parts of the vehicle, at least one classification of damage to the vehicle based on at least the plurality of images, wherein each classifier is generic with respect to a make and model of the vehicle;

outputting the determined classifications of the damage to the vehicle;

receiving claim input data comprising details of one or more proposed parts and labor operations for repairing the damage to the vehicle; and

verifying that the determined classifications of the damage to the vehicle correspond to the one or more proposed parts and labor operations for repairing the damage to the vehicle based on a confidence value associated with the determined classifications of the damage to the vehicle.

2 . The computer-implemented method of claim 1 , wherein verifying that the determined classifications of the damaged to the vehicle correspond to the one or more proposed parts and labor operations for repairing the damage to the vehicle comprises using one or more computer-implemented natural language processing models on the claim input data.

3 . The computer-implemented method of claim 1 , further comprising:

using one or more secondary classifiers trained on specific vehicle parts that is operable to generate damage representations of the specific vehicle parts from at least the plurality of images, wherein the specific vehicle parts are specific to any or any combination of a predetermined make, model and year of vehicle.

4 . The computer-implemented method of claim 1 , wherein at least a subset of the plurality of classifiers comprise a hierarchical arrangement.

5 . The computer-implemented method of claim 4 , wherein the hierarchical arrangement comprises at least three classifiers arranged hierarchically.

6 . The computer-implemented method of claim 4 , wherein the hierarchical arrangement further comprises one or more rules engines and/or databases.

7 . The computer-implemented method of claim 1 , wherein the one or more classifiers are configured to use rules specific to a jurisdiction, market or geography.

8 . The computer implemented method of claim 1 , wherein the one or more classifiers are configured to use a computer vision damage assessment model.

9 . The method of claim 1 , wherein the confidence value comprises a certainty of the prediction of the damage to the vehicle.

10 . A processor configured to perform operations, comprising:

receiving a plurality of images of the vehicle wherein some of the images comprise image data of damage to the vehicle;

determining, using one or more classifiers that are specific to a plurality of parts of the vehicle, at least one classification of damage to the vehicle based on at least the plurality of images, wherein each classifier is generic with respect to a make and model of the vehicle;

outputting the determined classifications of the damage to the vehicle;

receiving claim input data comprising details of one or more proposed parts and labor operations for repairing the damage to the vehicle; and

verifying that the determined classifications of the damage to the vehicle correspond to the one or more proposed parts and labor operations for repairing the damage to the vehicle based on a confidence value associated with the determined classifications of damage to the vehicle.

11 . The processor of claim 10 , wherein verifying that the determined classifications of the damaged to the vehicle correspond to the one or more proposed parts and labor operations for repairing the damage to the vehicle comprises using one or more computer-implemented natural language processing models on the claim input data.

12 . The processor of claim 10 , wherein the operations further comprise:

using one or more secondary classifiers trained on specific vehicle parts that is operable to generate damage representations of the specific vehicle parts from at least the plurality of images, wherein the specific vehicle parts are specific to any or any combination of a predetermined make, model and year of vehicle.

13 . The processor of claim 10 , wherein at least a subset of the plurality of classifiers comprise a hierarchical arrangement.

14 . The processor of claim 13 , wherein the hierarchical arrangement comprises at least three classifiers arranged hierarchically.

15 . The processor of claim 13 , wherein the hierarchical arrangement further comprises one or more rules engines and/or databases.

16 . The processor of claim 10 , wherein the one or more classifiers are configured to use rules specific to a jurisdiction, market or geography.

17 . The processor of claim 10 , wherein the one or more classifiers are configured to use a computer vision damage assessment model.

18 . A non-transitory computer readable storage medium comprising a set of executable instructions, wherein the executable instructions cause a processor to:

receive a plurality of images of the vehicle wherein some of the images comprise image data of damage to the vehicle;

determine, using one or more classifiers that are specific to a plurality of parts of the vehicle, at least one classification of damage to the vehicle based on at least the plurality of images, wherein each classifier is generic with respect to a make and model of the vehicle;

output the determined classifications of the damage to the vehicle;

receive claim input data comprising details of one or more proposed parts and labor operations for repairing the damage to the vehicle; and

verify that the determined classifications of the damage to the vehicle correspond to the one or more proposed parts and labor operations for repairing the damage to the vehicle based on a confidence value associated with the determined classifications of the damage to the vehicle.