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An Efficient Accelerator Design Methodology for Deformable Convolutional Networks
In this paper, we present a novel approach to accelerate deformable convolution on FPGA.
Towards Design Methodology of Efficient Fast Algorithms for Accelerating Generative Adversarial Networks on FPGAs
To implement the DeConv layer in hardware, the state-of-the-art accelerator reduces the high computational complexity via the DeConv-to-Conv conversion and achieves the same results.
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