Fanming Meng
Papers
1
Total Citations
5
H-Index
1
About
Fanming Meng is a researcher at the forefront of precision livestock farming, specializing in the integration of robotics, computer vision, and deep learning for agricultural automation. His work centers on developing lightweight, efficient models for real-time animal monitoring, with a particular focus on automated pig counting in intensive farming environments. Meng’s major contribution lies in significantly reducing computational demands without sacrificing accuracy—his most cited paper introduces a novel approach that replaces the traditional C2f module with a Ghost module within the YOLOv8n-seg framework, while incorporating a spatial group enhancement attention mechanism and a lightweight shared detail enhancement convolutional detection head. This innovation enables mobile inspection robots to perform reliable, on-site pig counting, addressing critical challenges in farm management and animal welfare. With over 5 citations for this 2025 publication, his work is gaining rapid recognition for its practical impact. Meng’s achievements demonstrate a powerful synergy between robotics and AI, offering scalable solutions that promise to transform modern agriculture through intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1