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US 11,308,363 B2Granted
Device and method for training an object detection model
AssigneeIntel Corporation
InventorsJulio Jarquin Arroyo, Kay-Ulrich Scholl
Life of this patent
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Abstract
A training device may include one or more processors configured to generate, using a data augmentation model, augmented sensor data for sensor data, the sensor data provided by a plurality of sensors, wherein the augmented sensor data comprise error states of one or more sensors of the plurality of sensors providing the sensor data, and to train an object detection model based on the augmented sensor data.
Claims20
A training device, comprising:
- one or more processors, configured to:
- generate, using a data augmentation model, augmented sensor data for sensor data, the sensor data provided by a plurality of sensors, wherein the augmented sensor data comprise error states of one or more sensors of the plurality of sensors providing the sensor data;
- and
- train an object detection model based on the augmented sensor data, wherein the object detection model comprises a plurality of feature extraction models, and wherein the one or more processors are configured to:
- determine, based on the plurality of feature extraction models, a plurality of features for the augmented sensor data;
- and
- train the object detection model based on the plurality of features, wherein the one or more processors are configured to train the object detection model by suppressing one or more selected features of the plurality of features, wherein the one or more selected features comprises all features associated with one or more selected sensors.
4 more elements
A device, comprising one or more processors, the one or more processors configured to:
- generate, using a data augmentation model, augmented sensor data for sensor data, the sensor data provided by a plurality of sensors, wherein the augmented sensor data comprise error states of one or more sensors of the plurality of sensors providing the sensor data;
- train an object detection model based on the augmented sensor data, wherein the object detection model comprises a plurality of feature extraction models, and wherein the one or more processors are configured to:
- determine, based on the plurality of feature extraction models, a plurality of features for the augmented sensor data;
- and
- train the object detection model based on the plurality of features, wherein the one or more processors are configured to train the object detection model by suppressing one or more selected features of the plurality of features, wherein the one or more selected features comprises all features associated to one or more selected sensors;
- generate training data using the trained object detection model;
- and
- train an additional model using the training data.
5 more elements
A non-transitory computer-readable medium comprising instructions recorded thereon which, when executed by one or more processors, cause the one or more processors to:
- generate, using a data augmentation model, augmented sensor data for sensor data, the sensor data provided by a plurality of sensors, wherein the augmented sensor data comprise error states of one or more sensors of the plurality of sensors providing the sensor data;
- and
- train an object detection model based on the augmented sensor data, wherein the object detection model comprises a plurality of feature extraction models, and wherein the one or more processors are configured to:
- determine, based on the plurality of feature extraction models, a plurality of features for the augmented sensor data;
- and
- train the object detection model based on the plurality of features, wherein the one or more processors are configured to train the object detection model by suppressing one or more selected features of the plurality of features, wherein the one or more selected features comprises all features associated with one or more selected sensors.
3 more elements
A non-transitory computer-readable medium comprising instructions recorded thereon which, when executed by one or more processors, cause the one or more processors to:
- generate, using a data augmentation model, augmented sensor data for sensor data, the sensor data provided by a plurality of sensors, wherein the augmented sensor data comprise error states of one or more sensors of the plurality of sensors providing the sensor data;
- and
- train an object detection model based on the augmented sensor data, wherein the object detection model comprises a plurality of feature extraction models, and wherein the one or more processors are configured to:
- determine, based on the plurality of feature extraction models, a plurality of features for the augmented sensor data;
- and
- train the object detection model based on the plurality of features, wherein the one or more processors are configured to train the object detection model by suppressing one or more selected features of the plurality of features, wherein the one or more selected features comprises all features associated with one or more selected sensors;
- generate training data using the trained object detection model;
- and
- train an additional model using the training data.
6 more elements
Dependencies are inferred from the claim text.