2016
Learning separable fixed-point kernels for deep convolutional neural networks
ICASSP 2016accepted
Deep convolutional neural networks have shown outstanding performance in several speech and image recognition tasks. However they demand high computational complexity which limits their deployment in resource limited machines. The proposed work lowers the hardware complexity by constraining the lear…