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Dual Path Binary Neural Network
- Source :
- ISOCC
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Binary neural networks can effectively reduce the number of required parameters but might decrease the classification accuracy. To solve the problem, we propose a dual-path binary neural network (DPBNN) in this paper. Experimental results show that our DPBNN can outperform other traditional binary neural network in CIFAR-10 and SVHN dataset. The proposed network is simple, so it is suitable to be implemented on embedded systems or SoC designs.
Details
- Database :
- OpenAIRE
- Journal :
- 2019 International SoC Design Conference (ISOCC)
- Accession number :
- edsair.doi...........f55f7485c4e56c29d7652fe6505bbde0