MixConv

2000년 도입 · 논문 12편에서 사용

MixConv, 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.

출처: MixConv: Mixed Depthwise Convolutional Kernels

소개 논문: MixConv: Mixed Depthwise Convolutional Kernels