Method and system for separating and recalibrating feature for adversarial robustness
AssigneeKorea Advanced Institute of Science and Technology
InventorsSung-Eui Yoon, Woo Jae Kim, Yoonki Cho, Junsik Jung
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Abstract
Disclosed is a method and system for separating and recalibrating a feature for adversarial robustness. A feature separation and recalibration method may include disentangling an input feature map into a first feature defined as a robust feature and a second feature defined as a non-robust feature, based on a robustness score; generating a recalibrated feature by recalibrating activation of the second feature; and generating an output feature map by combining the first feature and the recalibrated feature.
Claims19
A feature separation and recalibration method of a computer device comprising at least one processor, comprising:
- disentangling, by the at least one processor, an input feature map into a first feature defined as a robust feature and a second feature defined as a non-robust feature, based on a robustness score;
- generating, by the at least one processor, a recalibrated feature by recalibrating activation of the second feature;
- and
- generating, by the at least one processor, an output feature map by combining the first feature and the recalibrated feature.
A non-transitory computer-readable recording medium storing instructions that, when executed by a processor, cause the processor to perform a feature separation and recalibration method on a computer device, the feature separation and recalibration method comprising:
- disentangling an input feature map into a first feature defined as a robust feature and a second feature defined as a non-robust feature, based on a robustness score;
- generating a recalibrated feature by recalibrating activation of the second feature;
- and
- generating an output feature map by combining the first feature and the recalibrated feature.
A computer device comprising:
- at least one processor configured to execute a computer-readable instruction,
- wherein the at least one processor is configured to,
- disentangle an input feature map into a first feature defined as a robust feature and a second feature defined as a non-robust feature, based on a robustness score,
- generate a recalibrated feature by recalibrating activation of the second feature, and
- generate an output feature map by combining the first feature and the recalibrated feature.
Dependencies are inferred from the claim text.