Vector Quantization of Deep Convolutional Neural Networks With Learned Codebook-Reference-Cited by-同舟云学术

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Vector Quantization of Deep Convolutional Neural Networks With Learned Codebook

Published:2022-06-05 Issue: Volume: Page:
ISSN:
Container-title:2022 17th Canadian Workshop on Information Theory (CWIT)
language:
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Author:

Yang Siyuan¹,Mao Yongyi¹

Affiliation:

1. University of Ottawa,School of Electrical and Computer Engineering,Ottawa,ON,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9817614/9817658/09817671.pdf?arnumber=9817671

Reference30 articles.

1. Any-Precision Deep Neural Networks;haichao;AAAI,2021

2. Learning Filter Basis for Convolutional Neural Network Compression;yawei;ICCV,2019

3. Learning both Weights and Connections for Efficient Neural Networks;han;CoRR,2015

4. Pruning and quantization for deep neural network acceleration: A survey

5. Learning both Weights and Connections for Efficient Neural Network;song;NIPS,2015

Cited by 2 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. A deep learning based multi-image compression technique;Signal, Image and Video Processing;2024-04-22

2. A Codebook Compression Method for Vector Quantization Algorithm;Proceedings of Engineering and Technology Innovation;2024-02-29

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