Corpus ID: 210700033

MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy?

@article{Bethge2020MeliusNetCB,
  title={MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy?},
  author={Joseph Bethge and C. Bartz and Haojin Yang and Y. Chen and C. Meinel},
  journal={ArXiv},
  year={2020},
  volume={abs/2001.05936}
}

Joseph Bethge, C. Bartz, +2 authors C. Meinel

Published 2020

Computer Science, Mathematics

ArXiv

Binary Neural Networks (BNNs) are neural networks which use binary weights and activations instead of the typical 32-bit floating point values. They have reduced model sizes and allow for efficient inference on mobile or embedded devices with limited power and computational resources. However, the binarization of weights and activations leads to feature maps of lower quality and lower capacity and thus a drop in accuracy compared to traditional networks. Previous work has increased the number… CONTINUE READING

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