SegPGD: an effective and efficient adversarial attack for evaluating and boosting segmentation robustness
Deep neural network-based image classifications are vulnerable to adversarial perturbations. The image classifications can be easily fooled by adding artificial small and imperceptible perturbations to input images. As one of the most effective defense strategies, adversarial training was proposed t...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Springer
2022
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