FEGW-YOLO: A Feature-Complexity-Guided Lightweight Framework for Real-Time Multi-Crop Detection with Advanced Sensing Integration on Edge Devices
- DOI
- 10.3390/s26041313
- Published
- 2026-02-18
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s26041313,
title = {FEGW-YOLO: A Feature-Complexity-Guided Lightweight Framework for Real-Time Multi-Crop Detection with Advanced Sensing Integration on Edge Devices},
author = {Yaojiang Liu and Hongjun Tian and Yijie Yin and Yuhan Zhou and Wei Li and Yang Xiong and Yichen Wang and Zinan Nie and Yang Yang and Dongxiao Xie and Shijie Huang},
year = {2026},
journal = {Sensors},
doi = {10.3390/s26041313},
url = {https://doi.org/10.3390/s26041313}
}RIS
TY - JOUR TI - FEGW-YOLO: A Feature-Complexity-Guided Lightweight Framework for Real-Time Multi-Crop Detection with Advanced Sensing Integration on Edge Devices AU - Yaojiang Liu AU - Hongjun Tian AU - Yijie Yin AU - Yuhan Zhou AU - Wei Li AU - Yang Xiong AU - Yichen Wang AU - Zinan Nie AU - Yang Yang AU - Dongxiao Xie AU - Shijie Huang PY - 2026 JO - Sensors DO - 10.3390/s26041313 UR - https://doi.org/10.3390/s26041313 ER -
APA
Liu, Y., Tian, H., Yin, Y., Zhou, Y., Li, W., Xiong, Y., Wang, Y., Nie, Z., Yang, Y., Xie, D., & Huang, S. (2026). FEGW-YOLO: A Feature-Complexity-Guided Lightweight Framework for Real-Time Multi-Crop Detection with Advanced Sensing Integration on Edge Devices. Sensors. https://doi.org/10.3390/s26041313
Source records
- crossref · retrieved 2026-09-26T21:11:18.421Z