Lightweight Backbone Dominance | VGNetG Achieves ‘Want It All Without Choices’ Lightweight Backbone Network!
Modern efficient convolutional neural networks (CNN) always use depthwise separable convolutions (DSC) and neural architecture search (NAS) to reduce the number of parameters and computational complexity. However, they overlook some inherent features of the network. Inspired by visual feature maps and N×N (N>1) convolution kernels, this paper introduces several guidelines to further improve parameter efficiency … Read more