We propose an efficient deep convolutional neural network for a super‐resolution which is capable of multiple‐quality input, by analyzing the input quality and choosing appropriate features automatically. To implement the network in an FPGA and an ASIC, we employ a network trimming technique to compress the neural network.

中文翻译：

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使用深度卷积神经网络实现FPGA的高效多质量超分辨率

我们通过分析输入质量并自动选择合适的特征，为超分辨率提出了一种有效的深度卷积神经网络，该网络能够进行多种质量的输入。为了在FPGA和ASIC中实现网络，我们采用网络调整技术来压缩神经网络。