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Convolution Accelerator Designs Using Fast Algorithms
2019
Algorithms
Convolutional neural networks (CNNs) have achieved great success in image processing. However, the heavy computational burden it imposes makes it difficult for use in embedded applications that have limited power consumption and performance. Although there are many fast convolution algorithms that can reduce the computational complexity, they increase the difficulty of practical implementation. To overcome these difficulties, this paper proposes several convolution accelerator designs using
doi:10.3390/a12050112
fatcat:sb276imvbvglree2dqwcnptuga