Convolutions
Mixed Depthwise Convolution
Introduced by Tan et al. in MixConv: Mixed Depthwise Convolutional KernelsMixConv, or Mixed Depthwise Convolution, is a type of depthwise convolution that naturally mixes up multiple kernel sizes in a single convolution. It is based on the insight that depthwise convolution applies a single kernel size to all channels, which MixConv overcomes by combining the benefits of multiple kernel sizes. It does this by partitioning channels into groups and applying a different kernel size to each group.
Source: MixConv: Mixed Depthwise Convolutional Kernels
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Classification | 3 | 18.75% |
| Image Enhancement | 1 | 6.25% |
| Image Restoration | 1 | 6.25% |
| Low-Light Image Enhancement | 1 | 6.25% |
| Scene Text Detection | 1 | 6.25% |
| Text Detection | 1 | 6.25% |
| Automatic Speech Recognition (ASR) | 1 | 6.25% |
| Speech Recognition | 1 | 6.25% |
| Object Tracking | 1 | 6.25% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
