AMS-YOLO: multi-scale feature integration for intelligent plant protection against maize pests
The proposed AMS-YOLO model successfully addresses key challenges in maize pest detection through targeted architectural improvements. The lightweight design enables extended field deployment while maintaining high detection accuracy, making it highly suitable for resource-constrained agricultural environments. This advancement demonstrates significant potential for supporting more targeted pest management decisions, contributing to precision pesticide application and resource optimization in field conditions, thereby advancing intelligent and sustainable plant protection.
Authors
- Aziz Ullah (ORCID: https://orcid.org/0000-0002-3058-3476)
- Leilei Deng (ORCID: https://orcid.org/0009-0008-8993-5270)
- Fang Di (ORCID: https://orcid.org/0009-0005-6205-3639)
- Helong Yu
- Qi Hou
Institutions
- Changchun University of Science and Technology (CN)
- Jilin Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-10-03
- DOI
- https://doi.org/10.3389/fpls.2025.1640405
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75