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MobileNetV2 is a convolutional neural network

MobileNetV2 is a convolutional neural network Grq1x

MobileNetV2 is a convolutional neural network architecture that is 53 layers deep that seeks to perform well on mobile devices. It is based on an inverted residual structure where the residual connections are between the bottleneck layers. The intermediate expansion layer uses lightweight depthwise convolutions to filter features as a source of non-linearity. As a whole, the architecture of MobileNetV2 contains the initial fully convolution layer with 32 filters, followed by 19 residual bottleneck layers, this pre-trained network can classify images into 1000 object categories. The network has an image input size of 224-by-224.

MobileNetV2 is a convolutional neural network architecture that is
 53 You use this word too often, consider replacing it withsheetfloorcoatblanketbedthickness
layers
 deep that seeks to perform well on mobile devices. It is based
 on an inverted residual structure where the residual connections are between the bottleneck You use this word too often, consider replacing it withsheetfloorcoatblanketbedthickness
layers
. The intermediate expansion You use this word too often, consider replacing it withsheetfloorcoatblanketbedthickness
layer
This phrase/word (depending on the context) can be potentially replaced with :exploits
uses
 lightweight Possible spelling mistake found.depth wise
depthwise
 convolutions to filter features as a source of non-linearity. As a whole, the architecture of MobileNetV2 contains the initial fully
 convolution You use this word too often, consider replacing it withsheetfloorcoatblanketbedthickness
layer
 with 32 filters, followed by 19 residual bottleneck You use this word too often, consider replacing it withsheetfloorcoatblanketbedthickness
layers
, this pre-trained network can classify images into 1000 object categories. The network has an image input size of 224-by-224. 