Convolutional Neural Networks


Introduced by Gholami et al. in SqueezeNext: Hardware-Aware Neural Network Design

SqueezeNeXt is a type of convolutional neural network that uses the SqueezeNet architecture as a baseline, but makes a number of changes. First, a more aggressive channel reduction is used by incorporating a two-stage squeeze module. This significantly reduces the total number of parameters used with the 3×3 convolutions. Secondly, it uses separable 3 × 3 convolutions to further reduce the model size, and removes the additional 1×1 branch after the squeeze module. Thirdly, the network use an element-wise addition skip connection similar to that of ResNet architecture.

Source: SqueezeNext: Hardware-Aware Neural Network Design


Paper Code Results Date Stars