Using a GAN discriminator for anomaly detection
AssigneeToyota Jidosha Kabushiki Kaisha
InventorsDimitar H. Lukarski, Ryan M. Wiesenberg, Jeffrey M. Walls
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Abstract
Systems, methods, and other embodiments described herein relate to improving the accuracy of sensor data by using a discriminator to identify the presence of anomalies. In one embodiment, a method includes acquiring sensor data about a roadway. The method includes determining a presence of an anomaly within the sensor data using a discriminator from a generative adversarial network (GAN). The method includes generating an indicator for the sensor data according to whether the anomaly is present. The method includes providing the indicator with the sensor data.
Claims20
A detection system for identifying anomalies, comprising:
- one or more processors;
- a memory communicably coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the one or more processors to:
- acquire sensor data about a roadway;
- determine a presence of an anomaly within the sensor data using a discriminator from a generative adversarial network (GAN), wherein the anomaly is an aberration within the sensor data associated with an error in perceiving the roadway;
- generate an indicator for the sensor data according to whether the anomaly is present;
- and
- provide the indicator with the sensor data.
A non-transitory computer-readable medium including instructions that, when executed by one or more processors, cause the one or more processors to:
- acquire sensor data about a roadway;
- determine a presence of an anomaly within the sensor data using a discriminator from a generative adversarial network (GAN), wherein the anomaly is an aberration within the sensor data associated with an error in perceiving the roadway;
- generate an indicator for the sensor data according to whether the anomaly is present;
- and
- provide the indicator with the sensor data.
A method, comprising:
- acquiring sensor data about a roadway;
- determining a presence of an anomaly within the sensor data using a discriminator from a generative adversarial network (GAN), wherein the anomaly is an aberration within the sensor data associated with an error in perceiving the roadway;
- generating an indicator for the sensor data according to whether the anomaly is present;
- and
- providing the indicator with the sensor data.
Dependencies are inferred from the claim text.