LWheatNet: a lightweight convolutional neural network with mixed attention mechanism for wheat seed classification
The LWheatNet model proposed in this paper maintains high recognition accuracy while occupying minimal storage space. This makes it well-suited for real-time classification and recognition of wheat seed images on low-performance devices in the future.
Authors
- Qiao Zhu (ORCID: https://orcid.org/0000-0002-1828-7658)
- Zihao Cheng (ORCID: https://orcid.org/0009-0007-4729-3540)
- Guohong Gao (ORCID: https://orcid.org/0000-0001-6923-7178)
- Zhanpeng Ma (ORCID: https://orcid.org/0000-0003-0963-9241)
- Xing Wang (ORCID: https://orcid.org/0000-0001-8704-7861)
- Xiaojuan Guo (ORCID: https://orcid.org/0009-0007-9988-190X)
- Ranran Zhang (ORCID: https://orcid.org/0000-0003-2404-6559)
- Jianping Wang
Institutions
- Henan Institute of Science and Technology (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-01-10
- DOI
- https://doi.org/10.3389/fpls.2024.1509656
- Citations
- 4
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 7.00