| CPC G06V 20/56 (2022.01) [G01S 17/931 (2020.01); G05D 1/0088 (2013.01); G05D 1/0221 (2013.01); G06F 18/2163 (2023.01); G06F 18/217 (2023.01); G06F 18/24 (2023.01); G06N 20/00 (2019.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01)] | 20 Claims |

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1. A computer-implemented method, the method comprising:
obtaining sensor data representative of a secondary environment proximate to an autonomous vehicle;
generating an intermediate representation for the autonomous vehicle based, at least in part, on the sensor data, wherein the intermediate representation is descriptive of at least a portion of the secondary environment;
determining an intermediate representation deviation for the intermediate representation based, at least in part, on the intermediate representation and a machine-learned model associated with the autonomous vehicle, by:
obtaining, via the machine-learned model, one or more ground truth bounding box proposals based, at least in part, on the intermediate representation,
obtaining, via the machine-learned model, one or more deviating bounding box proposals, and
determining the intermediate representation deviation for the intermediate representation based, at least in part, on a comparison between the one or more ground truth bound box proposals and the one or more deviating bounding box proposals;
generating data indicative of a modified intermediate representation based, at least in part, on the intermediate representation and the intermediate representation deviation; and
communicating the data indicative of the modified intermediate representation to a vehicle computing system associated with the autonomous vehicle.
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