Publications by authors named "D DELAHAYE"

Article Synopsis
  • - Despite their success, deep learning models struggle with robustness, especially against adversarial attacks, which raises concerns about their reliability in critical applications.
  • - The paper proposes an information geometric framework to set clear robustness standards for l2 white-box attacks in multi-class classifications, using the Fisher information metric and specific criteria for the input-output Jacobian.
  • - The proposed method shows significant enhancements in model robustness on MNIST and CIFAR-10 datasets against various adversarial attacks, outperforming existing techniques like defensive distillation and Jacobian regularization, while still achieving high accuracy.
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Objectives: Patient Blood Management (PBM) is defined as a patient-centered, systematic, evidence-based approach to improve patient outcomes by managing and preserving a patient's own blood, while promoting patient safety and empowerment. As a corollary, it also reduces the utilization of allogeneic blood components. However, demonstrating cost-effectiveness depends on the health insurance system considered.

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The number of vehicles equipped with radars on the road has been increasing for years and is expected to reach 50% of cars by 2030. This rapid rise in radars will likely increase the risk of harmful interference, especially since radar specifications from standardization bodies (e.g.

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The COVID-19 pandemic has had a significant impact on the air transportation system worldwide. This paper aims at analyzing the effect of the travel restriction measures implemented during the COVID-19 pandemic from a passenger perspective on the US air transportation system. Four metrics based on data generated by passengers and airlines on social media are proposed to measure how the travel restriction measures impacted the relation between passengers and airlines in close to real-time.

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During the COVID-19 period and particularly during lockdown, deviations from nominal operations have shown to become more frequent. To confirm this observation this paper proposes to evaluate the impact of COVID-19, and more generally of crises that lead to a sharp drop in traffic, on the pilot/controller system, especially during the critical approach and landing phases. To study the influence of this type of crisis on flight operations at Charles De Gaulle airport, an existing energy atypicality metric is applied on a reference period before COVID-19 and compared to the COVID-19 period.

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