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Exploring robust architectures for deep artificial neural networks - Communications Engineering

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Exploring robust architectures for deep artificial neural networks - Communications Engineering

The architectures of deep artificial neural networks (DANNs) are routinely studied to improve their predictive performance. However, the relationship between the architecture of a DANN and its robustness to noise and adversarial attacks is less explored, especially in computer vision applications. Here we investigate the relationship between the robustness of DANNs in a vision task and their underlying graph architectures or structures.

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Exploring robust architectures for deep artificial neural networks - Communications Engineering

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Exploring robust architectures for deep artificial neural networks - Communications Engineering

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