yolov8-wogan
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
Found CITATION.cff file -
✓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 (0.4%) to scientific vocabulary
Last synced: 6 months ago
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JSON representation
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Repository
Basic Info
- Host: GitHub
- Owner: Mo-Outro
- License: agpl-3.0
- Language: Python
- Default Branch: master
- Size: 3.64 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 6
- Releases: 0
Created over 1 year ago
· Last pushed over 1 year ago
Metadata Files
Readme
Contributing
License
Citation
README.md
A high-accuracy and lightweight improved YOLOv8n model for detecting ‘Wogan’ citrus fruits in complex orchard environments was proposed, and it has been successfully deployed on an edge device.
Owner
- Login: Mo-Outro
- Kind: user
- Repositories: 1
- Profile: https://github.com/Mo-Outro
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
type: software
message: If you use this software, please cite it as below.
authors:
- family-names: Jocher
given-names: Glenn
orcid: "https://orcid.org/0000-0001-5950-6979"
- family-names: Chaurasia
given-names: Ayush
orcid: "https://orcid.org/0000-0002-7603-6750"
- family-names: Qiu
given-names: Jing
orcid: "https://orcid.org/0000-0003-3783-7069"
title: "YOLO by Ultralytics"
version: 8.0.0
# doi: 10.5281/zenodo.3908559 # TODO
date-released: 2023-1-10
license: AGPL-3.0
url: "https://github.com/ultralytics/ultralytics"