seca
Global Interpretation of Image Classification Models via SEmantic Feature Analysis (SEFA)
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (2.7%) to scientific vocabulary
Last synced: 6 months ago
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Repository
Global Interpretation of Image Classification Models via SEmantic Feature Analysis (SEFA)
Basic Info
- Host: GitHub
- Owner: delftcrowd
- Language: Jupyter Notebook
- Default Branch: master
- Homepage: https://delftcrowd.github.io/SECA/intro.html
- Size: 12 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 6
- Releases: 0
Created about 4 years ago
· Last pushed about 4 years ago
Metadata Files
Readme
Changelog
Contributing
Citation
README.md
Global Interpretability via SEmantic Concept extraction and Analysis (SECA)
Purpose of software
Installation instructions
Users
Developers
Contributing guidelines
Owner
- Name: TU Delft Crowd Computing Team (Kappa)
- Login: delftcrowd
- Kind: organization
- Repositories: 4
- Profile: https://github.com/delftcrowd
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Agathe"
given-names: "Balayn"
orcid: "https://orcid.org/0000-0000-0000-0000"
title: "SECA"
version: 0.0.1
doi:
date-released:
url: "https://github.com/delftcrowd/SECA"
keywords:
- "machine learning"
- "explainability"
GitHub Events
Total
Last Year
Dependencies
conda/environment.yml
pypi
- saliency *
- symspellpy *
jupyter_book/requirements.txt
pypi
- jupyter-book *
- matplotlib *
- numpy *
setup.py
pypi
- graphviz *
- keras *
- matplotlib *
- mlxtend *
- notebook *
- numpy *
- pandas *
- saliency *
- scikit-image *
- scikit-learn *
- scipy *
- symspellpy *
- tensorflow *