MoGA-A

Introduced by Chu et al. in MoGA: Searching Beyond MobileNetV3

MoGA-A is a convolutional neural network optimized for mobile latency and discovered via Mobile GPU-Aware (MoGA) neural architecture search. The basic building block is MBConvs (inverted residual blocks) from MobileNetV2. Squeeze-and-excitation layers are also experimented with.

Source: MoGA: Searching Beyond MobileNetV3

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Papers

Paper	Code	Results	Date	Stars

Tasks

Task	Papers	Share
Image Classification	1	100.00%

Usage Over Time

This feature is experimental; we are continuously improving our matching algorithm.

Components

Component	Type	Add Remove
1x1 Convolution	Convolutions
Convolution	Convolutions
Dense Connections	Feedforward Networks
Global Average Pooling	Pooling Operations
Inverted Residual Block	Skip Connection Blocks
Softmax	Output Functions
Squeeze-and-Excitation Block	Image Model Blocks

Categories

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Convolutional Neural Networks

Light-weight neural networks