Kernel Quantization for Efficient Network Compression
This paper presents a novel network compression framework, <bold>Kernel Quantization</bold> (<bold><italic>KQ</italic></bold>), targeting to efficiently convert any pre-trained full-precision convolutional neural network (CNN) model into a low-precision version wi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9672186/ |