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Keyword: Ghost module ×Clear all

1 claim from 1 paper

1. Computer Science › Advanced Neural Network Applications

   GhostNet: More Features from Cheap Operations

   Han, Wang, Tian, Guo, Xu and Xu · arXiv (Cornell University) · 2019

   The paper proposes the Ghost module, which makes extra feature maps from cheap operations, and uses it to build GhostNet, a lightweight image-recognition network for devices with limited resources.

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   1. UncheckedThe paper reports that its Ghost module can replace standard convolution layers, and GhostNet reached 75.7% top-1 on ImageNet, beating MobileNetV3 at similar cost.“Experiments conducted on benchmarks demonstrate that the proposed Ghost module is an impressive alternative of convolution layers in baseline models, and our GhostNet can achieve higher recognition performance (e.g. $75.7\%$ top-1 accuracy) than MobileNetV3 with similar computational cost on the Im…”