MobileNet v1 - AshokBhat/ml GitHub Wiki

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MobileNet v1 vs ResNet-50 v1.5

  • Reduces the parameters by 6.1x
  • Reduces operations by 6.8x

Paper

  • MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Abstract

We present a class of efficient models called [MobileNet]] for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses [depth-wise separable convolutions to build lightweight deep neural networks.

We introduce two simple global [hyperparameter]]s that efficiently trade-off between latency and [[accuracy]]. These [hyper-parameters allow the model builder to choose the right sized model for their application based on the constraints of the problem.

We present extensive experiments on resource and accuracy tradeoffs and show strong performance compared to other popular models on ImageNet classification. We then demonstrate the effectiveness of MobileNets across a wide range of applications and use cases including object detection, fine-grain classification, face attributes, and large scale geo-localization

See also