surveygreenai
Science Score: 57.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○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 (8.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Cimagroup
- License: apache-2.0
- Language: Python
- Default Branch: main
- Size: 3.37 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
Beta Version - Data Reduction Repository
This is the beta version of the data reduction package created by the CIMAgroup research team at the University of Seville, Spain, for the European Project REXASI-PRO (REliable & eXplainable Swarm Intelligence for People with Reduced mObility) (HORIZON-CL4-HUMAN-01 programme under grant agreement nº101070028).
This repository reunites in a single package a list of data reduction techniques:
- SRS: Stratified Random Sampling
- PRD: ProtoDash Selection
- CLC: Clustering Centroids Selection
- MMS: Maxmin Selection
- DES: Distance-Entropy Selection
- PHL: Persistent Homology Landmarks Selection
- NRMD: Numerosity Reduction by Matrix Decomposition
- FES: Forgetting Events Selection
To use the data reduction functions, it is necessary to install a list of libraries and clone the original repositories of the papers we are referencing to. To clone them, it is necessary to
Installation in Windows
- Create a virtual environment with Python >=3.9
- Install GitBash (https://git-scm.com/downloads).
- Open a terminal and execute in "datareduction/OriginalRepositories":
bash
./clone_repos.bat
4. To conclude the installation, go to the same location as setup.py and execute in a terminal:
bash
./install.bat
Installation in Ubuntu
- Install GitBash (https://git-scm.com/downloads).
- Open a terminal and execute in "datareduction/OriginalRepositories":
bash
chmod +x ./clone_repos.sh
./clone_repos.sh
- Create a virtual environment for Python version 3.9 or higher.
bash
conda create -n name python=3.9
conda activate name
- To conclude the installation, go to the same location as setup.py and execute in a terminal:
bash
chmod +x ./install.sh
sed -i -e 's/\r$//' install.sh
./install.sh
Citation and reference
If you want to use our code for your experiments, please cite our paper as fpllows:
Perera-Lago J, Toscano-Duran V, Paluzo-Hidalgo E et al. An in-depth analysis of data reduction methods for sustainable deep learning [version 2; peer review: 2 approved]. Open Res Europe 2024, 4:101 (https://doi.org/10.12688/openreseurope.17554.2)
For further information, please contact us at: vtoscano@us.es jperera@us.es
Owner
- Name: Combinatorial Image Analysis research group
- Login: Cimagroup
- Kind: organization
- Website: http://grupo.us.es/cimagroup/
- Repositories: 1
- Profile: https://github.com/Cimagroup
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Repository Survey Green AI
message: 'If you use this software, please cite it as below.'
type: software
authors:
- given-names: Javier
family-names: Perera Lago
email: jperera@us.es
affiliation: Universidad de Sevilla
orcid: 'https://orcid.org/0000-9000-9453-6402'
- given-names: Eduardo
family-names: Paluzo Hidalgo
email: epaluzo@uloyola.es
affiliation: Universidad de Loyola
orcid: 'https://orcid.org/0000-0002-4280-5945'
- given-names: Víctor
family-names: Toscano Durán
email: vtoscano@us.es
affiliation: Universidad de Sevilla
orcid: 'https://orcid.org/0009-0006-1316-9026'
identifiers:
- type: doi
value: 10.5281/zenodo.10844558
repository-code: 'https://github.com/Cimagroup/SurveyGreenAI/'
version: '1.0'
date-released: '2024-03-20'
GitHub Events
Total
Last Year
Dependencies
- GitPython ==3.1.36
- cvxopt ==1.3.2
- cvxpy ==1.4.1
- cython ==3.0.2
- gudhi ==3.9.0
- mnist ==0.2.2
- numpy ==1.23.5
- openpyxl ==3.0.10
- pandas ==1.3.5
- pyspark ==3.5.0
- qpsolvers ==4.0.1
- scikit-learn ==1.3.0
- scipy ==1.11.4
- tensorflow ==2.15.0
- xport ==3.6.1