Over the past 18 months or so, a number of new neural network achitectures were proposed specifically for use on mobile and edge devices. It seems that pretty much everyone has figured out now that large models such as VGG16 or ResNet-50 aren’t a good idea on small devices. 😉 I have previously written about MobileNet v1 and v2 , and have used these models in many client projects. But it’s 2020 and there are new kids on the block! In this blog post we’ll look at a number of these new neural network designs and do some speed measurements to see how fast they are. First we’ll revisit a few older architectures: SqueezeNet MobileNet v1 MobileNet v2 And then we’ll look at the new ones: MnasNet MobileNet v3 BlazeFace TinyYOLO / Darknet SqueezeNext ShuffleNet CondenseNet ESPNet DiCENet FBNet & ChamNet GhostNet MixNet EfficientNet It’s possible I missed some architectures. Found an interesting architecture that isn’t covered here? Let me know and I’ll add it to the blog post. 
 链接地址： https://machinethink.net/blog/mobile-architectures/