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DEM: A Method for Certifying Deep Neural Network Classifier Outputs in Aerospace
Software development in the aerospace domain requires adhering to strict, high-quality standards.
gRoMA: a Tool for Measuring the Global Robustness of Deep Neural Networks
Multiple studies have demonstrated that even modern DNNs are susceptible to adversarial inputs, and this risk must thus be measured and mitigated to allow the deployment of DNNs in critical settings.
RoMA: a Method for Neural Network Robustness Measurement and Assessment
In this paper, we present a new statistical method, called Robustness Measurement and Assessment (RoMA), which can measure the expected robustness of a neural network model.
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