Explain MobileNet Architecture?

Data Science, AI and ML
#1

MobileNet uses depthwise separable convolutions. It significantly reduces the number of parameters when compared to the network with regular convolutions with the same depth in the nets. This results in lightweight deep neural networks.

As the name applied, the MobileNet model is designed to be used in mobile applications, and it is TensorFlow’s first mobile computer vision model. MobileNet uses depthwise separable convolutions. It significantly reduces the number of parameters when compared to the network with regular convolutions with the same depth in the nets. This results in lightweight deep neural networks.

A depthwise separable convolution is made from two operations.

  1. Depthwise convolution.
  2. Pointwise convolution.