Safety verification of deep neural networks
Deep neural networks have achieved impressive experimental results in image classification, but can surprisingly be unstable with respect to adversarial perturbations, that is, minimal changes to the input image that cause the network to misclassify it. With potential applications including percepti...
| Main Authors: | , , , |
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| Format: | Conference item |
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Springer
2017
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