Xingyue Gao
Papers
1
Total Citations
15
H-Index
1
About
Xingyue Gao is a leading researcher at the intersection of artificial intelligence and sustainable agriculture, with a primary focus on precision weed control technologies. Her work harnesses deep learning and machine vision to revolutionize automated vegetation management, addressing critical challenges in modern farming. Gao’s most cited paper, "Applications, Trends, and Challenges of Precision Weed Control Technologies Based on Deep Learning and Machine Vision" (2025), offers a comprehensive review of advanced computer vision and deep learning systems, analyzing their principles, designs, and integration into agricultural practices. This seminal work has already garnered 15 citations, underscoring its timely impact. By systematically evaluating the potential and obstacles of these technologies, Gao provides a roadmap for reducing herbicide use and enhancing crop yields through targeted, intelligent weed management. Her contributions are pivotal in bridging the gap between cutting-edge AI and real-world agricultural applications, making her a notable figure in the push toward sustainable, data-driven farming. For students and researchers, Gao’s work exemplifies how interdisciplinary innovation can tackle global food security challenges.
Research Focus
Key Achievements
Top Papers
- 1