Neuron-by-Neuron Quantization for Efficient Low-Bit QNN Training
Quantized neural networks (QNNs) are widely used to achieve computationally efficient solutions to recognition problems. Overall, eight-bit QNNs have almost the same accuracy as full-precision networks, but working several times faster. However, the networks with lower quantization levels demonstrat...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI
2023
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |