FR performance comparison

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation  arXiv:1801.04381v2 [cs.CV] 16 Jan 2018

Table 4: Performance on ImageNet, comparison for different networks. As is common practice for ops, we count the total number of Multiply-Adds. In the last column we report running time in milliseconds (ms) for a single large core of the Google Pixel 1 phone (using TF-Lite). We do not report ShuffleNet numbers as the framework does not yet support efficient group convolutions.