Vladimir Protsenko*

Quantization-Friendly Winograd Transformations for Convolutional Neural Networks

"Efficient deployment of modern deep convolutional neural networks on resource-constrained devices suffers from demanding computational requirements of convolution operations. Quantization and use of Winograd convolutions operating on sufficiently large-tile inputs are two powerful strategies to spe…