efficient-pruning-and-compression-techniques-for-cnns
Efficient Pruning and Compression Techniques for CNNs to Preserve Knowledge and Optimize Performance
https://github.com/j-skrzynski/efficient-pruning-and-compression-techniques-for-cnns
Science Score: 44.0%
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Low similarity (0.8%) to scientific vocabulary
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Efficient Pruning and Compression Techniques for CNNs to Preserve Knowledge and Optimize Performance
Basic Info
- Host: GitHub
- Owner: j-skrzynski
- Language: Jupyter Notebook
- Default Branch: main
- Size: 369 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 1 year ago
· Last pushed over 1 year ago
Metadata Files
Readme
Citation
README.md
Efficient-Pruning-and-Compression-Techniques-for-CNNs
Efficient Pruning and Compression Techniques for CNNs to Preserve Knowledge and Optimize Performance
Owner
- Login: j-skrzynski
- Kind: user
- Repositories: 1
- Profile: https://github.com/j-skrzynski
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Skrzyński
given-names: Jakub
orcid: https://orcid.org/0009-0008-4550-5009
- family-names: Horzyk
given-names: Adrian
orcid: https://orcid.org/0000-0001-9001-4198
title: "Efficient Pruning and Compression Techniques for Convolutional Neural Networks to Preserve Knowledge and Optimize Performance"
version: 1.0.0
url: "https://github.com/j-skrzynski/Efficient-Pruning-and-Compression-Techniques-for-CNNs"