An Adaptive Quantization Method for CNN Activations
Author:
Affiliation:
1. School of Microelectronics, Tianjin University,Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology,Tianjin,China,300072
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10181241/10181318/10181695.pdf?arnumber=10181695
Reference24 articles.
1. Overflow aware quantization: Accelerating neural network inference by low-bit multiply-accumulate operations;xie;Proceedings of the Twenty-Ninth international joint conference on Artificial Intelligence,2021
2. Wavelet Integrated CNNs for Noise-Robust Image Classification
3. Pact: Parameterized clipping activation for quantized neural networks;choi;ArXiv Preprint,2018
4. Per-channel Quantization Level Allocation for Quantizing Convolutional Neural Networks
5. Base-Reconfigurable Segmented Logarithmic Quantization and Hardware Design for Deep Neural Networks
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. AQA: An Adaptive Post-Training Quantization Method for Activations of CNNs;IEEE Transactions on Computers;2024-08
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