Wu Fan
Papers
1
Total Citations
8
H-Index
1
About
Wu Fan’s research lies at the intersection of artificial intelligence, robotics, and sports science, with a particular focus on the intelligent development of Sports and Leisure Characteristic Towns (SLCT). Their most-cited work, “Inheritance and Innovation Development of Sports Based on Deep Learning and Artificial Intelligence” (2023, 8 citations), introduces a novel approach to accelerating the smart construction of SLCTs by leveraging AI and robotic technologies. Specifically, Fan simplified and improved the MobileNetV2 architecture using robot technology to design a lightweight image recognition system, enabling efficient and scalable deployment in real-world sports and leisure environments. This contribution addresses a critical gap in integrating deep learning with physical infrastructure, offering a practical pathway for modernizing recreational spaces. By bridging advanced computational methods with applied sports development, Wu Fan’s work demonstrates significant potential for transforming how communities engage with sports and leisure through intelligent automation. Their research not only advances the field of AI-driven sports innovation but also provides a replicable framework for sustainable urban development.
Research Focus
Key Achievements
Top Papers
- 1