README.md

MobileNets Implementation

Implementing MobileNets in pytorch.
Welcome any advice with widely open arms.

Todo

• MobileNet version 1
• MobileNet version 2
• MobileNet version 3
• Training MobileNets on ImageNet Dataset...

Version 1

• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
• Authors
  • [Andrew G. Howard | Menglong Zhu | Bo Chen | Dmitry Kalenichenko | Weijun Wang | Tobias Weyand | Marco Andreetto | Hartwig Adam]
    
    
• [Paper] | [Code]
• Introduce a Depthwise convolution which is consist of two layers, depthwise and pointwise convolutions. It had similar performance to normal(original?) convolution, however it does have lower computation cost.

Version 2

• MobileNetV2: Inverted Residuals and Linear Bottlenecks
• Authors
  • [Mark Sandler | Andrew Howard | Menglong Zhu | Andrey Zhmoginov | Liang-Chieh Chen]
    
    
• [Paper] | [Code]
• Introduce a Inverted Residual and Linear Bottlenecks Relu is capable of preserving complete information about the input manifold, but only if the input manifold lies in a low-dimensional subspace. So, in MobileNet version 2, we are gonna use Inverted Residual block, which using relu in a lower dimension and expanding it into a higher dimension following a linear transformation. Using linear layers is crucial as it prevents non-linearities from destroying too much information.