Selective Kernel
Selective Kernel
A **Selective Kernel** unit is a bottleneck block consisting of a sequence of 1×1 [convolution](https://paperswithcode.com/method/convolution), SK convolution and 1×1 convolution. It was proposed as part of the [SKNet](https://paperswithcode.com/method/sknet) CNN architecture. In general, all the large kernel convolutions in the original bottleneck blocks in [ResNeXt](https://paperswithcode.com/method/resnext) are replaced by the proposed SK convolutions, enabling the network to choose appropriate receptive field sizes in an adaptive manner. 

In SK units, there are three important hyper-parameters which determine the final settings of SK convolutions: the number of paths $M$ that determines the number of choices of different kernels to be aggregated, the group number $G$ that controls the cardinality of each path, and the reduction ratio $r$ that controls the number of parameters in the fuse operator. One typical setting of SK convolutions is $\text{SK}\left[M, G, r\right]$ to be $\text{SK}\left[2, 32, 16\right]$.
Selective Kernel Networks
https://paperswithcode.com/paper/selective-kernel-networks
Selective Kernel Networks