Sept. 14, 2022, 1:20 a.m. | Yiming Li, Mingyan Zhu, Xue Yang, Yong Jiang, Shu-Tao Xia

cs.CR updates on arXiv.org arxiv.org

Deep learning, especially deep neural networks (DNNs), has been widely and
successfully adopted in many critical applications for its high effectiveness
and efficiency. The rapid development of DNNs has benefited from the existence
of some high-quality datasets ($e.g.$, ImageNet), which allow researchers and
developers to easily verify the performance of their methods. Currently, almost
all existing released datasets require that they can only be adopted for
academic or educational purposes rather than commercial purposes without
permission. However, there is still …

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