MobileNets Can Be Lossily Compressed: Neural Network Compression for Embedded Accelerators
Although neural network quantization is an imperative technology for the computation and memory efficiency of embedded neural network accelerators, simple post-training quantization incurs unacceptable levels of accuracy degradation on some important models targeting embedded systems, such as Mobile...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/6/858 |