Abstract: Non-exemplar class-incremental learning refers to continual classifying of new and old classes without storing samples of old classes. Since only new class samples are available, ...
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Abstract: Currently, deep neural networks (DNNs) are susceptible to adversarial attacks, particularly when the network's structure and parameters are known, while most of the existing attacks do not ...
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