that computer vision applications run well on mobile devices mobile nets used F Y separable convolutions in its 28 layer architecture this paper compares the performance of mobile nets with fully connected layers versus depth wise separable convolution layers it turns out the accuracy on image net only drops a 1% while using significantly less number of parameters from twenty nine point three million the number of parameters it's down to just 4.2 million we can see the mulch as the number of multiplications and additions which is a