Image Models
ProxylessNet-Mobile
Introduced by Cai et al. in ProxylessNAS: Direct Neural Architecture Search on Target Task and HardwareProxylessNet-Mobile is a convolutional neural architecture learnt with the ProxylessNAS neural architecture search algorithm that is optimized for mobile devices. It uses inverted residual blocks (MBConvs) from MobileNetV2 as its basic building block.
Source: ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Classification | 2 | 40.00% |
| Few-Shot Image Classification | 1 | 20.00% |
| General Classification | 1 | 20.00% |
| Language Modelling | 1 | 20.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
Convolution
|
Convolutions | |
Global Average Pooling
|
Pooling Operations | |
Inverted Residual Block
|
Skip Connection Blocks |
