Tight Compression: Compressing CNN Model Tightly Through Unstructured Pruning and Simulated Annealing Based Permutation-Reference-Cited by-同舟云学术

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Tight Compression: Compressing CNN Model Tightly Through Unstructured Pruning and Simulated Annealing Based Permutation

Published:2020-07 Issue: Volume: Page:
ISSN:
Container-title:2020 57th ACM/IEEE Design Automation Conference (DAC)
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Author:

Chen Xizi,Zhu Jingyang,Jiang Jingbo,Tsui Chi-Ying

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9211868/9218488/09218701.pdf?arnumber=9218701

Cited by 11 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. Streamlining YOLOv7 for Rapid and Accurate Detection of Rapeseed Varieties on Embedded Device;Sensors;2024-08-28

2. RCW-Pruner: Row-Column Wise Pruning Framework on Systolic Array;2024 10th IEEE International Conference on High Performance and Smart Computing (HPSC);2024-05-10

3. Optimizing Vision Transformers: Leveraging Max and Min Operations for Efficient Pruning;2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS);2024-04-22

4. A Review of Neural Network Lightweighting Techniques;Innovation & Technology Advances;2024-01-16

5. Applications of Pruning Methods in Natural Language Processing;IEEE Access;2024

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