XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
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- 17 September 2016
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- conference paper
- Published by Springer Science and Business Media LLC
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This publication has 13 references indexed in Scilit:
- Fast R-CNNPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Cross-Domain Synthesis of Medical Images Using Efficient Location-Sensitive Deep NetworkPublished by Springer Science and Business Media LLC ,2015
- Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete SynapsesPhysical Review Letters, 2015
- Going deeper with convolutionsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Fully convolutional networks for semantic segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Fixed point optimization of deep convolutional neural networks for object recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Fixed-point feedforward deep neural network design using weights +1, 0, and −1Published by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Rich Feature Hierarchies for Accurate Object Detection and Semantic SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Speeding up Convolutional Neural Networks with Low Rank ExpansionsPublished by British Machine Vision Association and Society for Pattern Recognition ,2014
- Approximation by superpositions of a sigmoidal functionMathematics of Control, Signals, and Systems, 1989