DSC-DeepLabv3+: a lightweight semantic segmentation model for weed identification in maize fields
These results demonstrate that DSC-DeepLabv3+ strikes an effective balance between accuracy and efficiency, outperforming several classical lightweight models, making it a promising solution for accurate and efficient weed segmentation in agricultural applications.
Authors
- Li Wen (ORCID: https://orcid.org/0000-0002-1498-3103)
- Xiaoyao Li (ORCID: https://orcid.org/0000-0002-4600-1215)
- Tuo Wu
- Yuxuan Feng (ORCID: https://orcid.org/0009-0003-7935-453X)
- Haitao Fu (ORCID: https://orcid.org/0000-0001-9673-6845)
- Li Zhu (ORCID: https://orcid.org/0000-0002-2532-2087)
- Xin Pan (ORCID: https://orcid.org/0000-0002-5640-697X)
Institutions
- BaiCheng Normal University (CN)
- Jilin Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-09-03
- DOI
- https://doi.org/10.3389/fpls.2025.1647736
- Citations
- 4
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 7.00