Abstract: In current class-agnostic counting research, models commonly suffer from reliance on external exemplars and high computational complexity, which limit their application in ...
Abstract: Deep neural networks (DNNs) have achieved satisfactory performance in multiple fields. However, recent studies have shown that DNNs can be easily fooled by adversarial examples. To mitigate ...
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