SqueezeNeXt Block

Computer VisionIntroduced 20003 papers
Source Paper

Description

A SqueezeNeXt Block is a two-stage bottleneck module used in the SqueezeNeXt architecture to reduce the number of input channels to the 3 × 3 convolution. We decompose with separable convolutions to further reduce the number of parameters (orange parts), followed by a 1 × 1 expansion module.

Papers Using This Method

HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision2019-04-29ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs2019-02-27SqueezeNext: Hardware-Aware Neural Network Design2018-03-23