GAP: Quantifying the Generative Adversarial Set and Class Feature Applicability of Deep Neural Networks - researchr publication

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Edward Collier, Supratik Mukhopadhyay. GAP: Quantifying the Generative Adversarial Set and Class Feature Applicability of Deep Neural Networks. In 25th International Conference on Pattern Recognition, ICPR 2020, Virtual Event / Milan, Italy, January 10-15, 2021. pages 8384-8391, IEEE, 2020. [doi]

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