qhnet
QHNet: A Novel Quad-Head Network for Real-Time Detection of Intruding Drones
Science Score: 57.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓DOI references
Found 1 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (8.3%) to scientific vocabulary
Repository
QHNet: A Novel Quad-Head Network for Real-Time Detection of Intruding Drones
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 5
- Releases: 0
Metadata Files
README.md
QHNet: A Novel Quad-Head Network for Real-Time Detection of Intruding Drones
Model Zoo
| Model | Resolution | Epoch | Params(M) | FLOPs(G) | $AP$ | $AP_{50}$ | $AP_{75}$ | BaiduYun Download | Google Download |
|---|---|---|---|---|---|---|---|---|---|
| QHNet-N | 640 | 200 | 2.8 | 12.0 | 57.1 | 88.9 | 65.9 | weight | --- |
| QHNet-S | 640 | 200 | 10.4 | 35.1 | 60.2 | 91.2 | 70.1 | weight | --- |
| QHNet-M | 640 | 200 | 17.9 | 71.1 | 62.1 | 92.8 | 71.4 | weight | --- |
| QHNet-L | 640 | 200 | 24.0 | 120.4 | 63.1 | 93.2 | 71.9 | weight | --- |
| QHNet-X | 640 | 200 | 37.1 | 183.8 | 64.0 | 93.8 | 74.3 | weight | --- |
- Results of the mAP are evaluated on the DUT-Plus dataset (an augmented version of the DUT-Anti-UAV dataset) with an input resolution of 640640.
- All models are trained without using pretrained weights.
Dependencies and Installation
- Clone and enter the repo.
shell
git clone https://github.com/wanq501/QHNet.git
cd QHNet
- Install dependencies
shell
pip install -e .
Training and Evaluation
- Training
shell
python tools/train.py
- Evaluation
shell
python tools/val.py
- Test
shell
python tools/test.py
- Detect
shell
python tools/detect.py
- Note: Each script includes detailed instructions on how to set parameters and use the script properly.
Citation
If you find our repo useful for your research, please cite us:
``` @ARTICLE{QHNet, author={Wan, Qian and Feng, Li and Xiao, Zhiwen and Zhu, Zonghai and Xing, Huanlai and Tian, Yunong and Feng, Yurui and Wei, Zong}, journal={IEEE Transactions on Geoscience and Remote Sensing}, title={QHNet: A Novel Quad-Head Network for Real-Time Detection of Intruding Drones}, year={2025}, doi={10.1109/TGRS.2025.3567751}}
```
This project is based on the open source codebase YOLO (Ultralytics).
@misc{YOLOv8,
author={Glenn Jocher and Ayush Chaurasia and Jing Qiu},
title={YOLOv8 by Ultralytics},
version={8.0.0},
year={2023},
month={jan},
license={AGPL-3.0},
url={https://github.com/ultralytics/ultralytics}
}
Owner
- Name: wanq
- Login: wanq501
- Kind: user
- Repositories: 1
- Profile: https://github.com/wanq501
Citation (CITATION.cff)
# This CITATION.cff file was generated with https://bit.ly/cffinit
cff-version: 1.2.0
title: Ultralytics YOLO
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Glenn
family-names: Jocher
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0001-5950-6979'
- given-names: Ayush
family-names: Chaurasia
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0002-7603-6750'
- family-names: Qiu
given-names: Jing
affiliation: Ultralytics
orcid: 'https://orcid.org/0000-0003-3783-7069'
repository-code: 'https://github.com/ultralytics/ultralytics'
url: 'https://ultralytics.com'
license: AGPL-3.0
version: 8.0.0
date-released: '2023-01-10'
GitHub Events
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Last Year
- Delete event: 5
- Issue comment event: 25
- Push event: 107
- Pull request event: 17
- Create event: 22