Papers
1
Total Citations
4
H-Index
1
About
Fu Xu is a researcher at the forefront of applying deep learning and sensor technology to forestry and environmental monitoring. His work centers on developing automated, non-invasive methods for measuring critical tree parameters, with a particular focus on stem diameter—a key metric for forest resource management and carbon stock estimation. Xu’s most cited paper, “An automated method for stem diameter measurement based on laser module and deep learning” (2023), introduces a novel device that combines an image sensor with a laser module to replace traditional, labor-intensive manual measurements. This innovation not only reduces the need for expert personnel but also cuts costs and time, making large-scale forest surveys more accessible. With 4 citations in a short time, this work is gaining traction among ecologists and forestry engineers. Xu’s contributions are notable for bridging the gap between computer vision and practical field applications, offering a scalable solution that could revolutionize how we monitor forest health and growth. His research is particularly valuable for students and researchers interested in the intersection of AI, environmental science, and sustainable resource management.
Research Focus
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Top Papers
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