Kernel Quantization for Efficient Network Compression

This paper presents a novel network compression framework, Kernel Quantization (KQ), targeting to efficiently convert any pre-trained full-precision convolutional neural network (CNN) model into a low-precision version without significant performance loss.Unlike existing methods struggling with weig... View More