Papers
1
Total Citations
31
H-Index
1
About
Xiaohu Wu is a leading researcher at the intersection of unmanned aerial vehicles (UAVs) and deep learning, with a primary focus on precision agriculture. His most-cited work, a comprehensive 2024 survey on UAVs and deep learning in precision agriculture (31 citations), synthesizes cutting-edge advances in remote sensing, crop monitoring, and automated decision-making for sustainable farming. Wu’s contributions are pivotal in demonstrating how drone-based imaging combined with neural networks can revolutionize yield prediction, pest detection, and resource optimization. His research bridges engineering and agronomy, offering scalable solutions for global food security. Beyond this flagship survey, Wu has published extensively on UAV path planning and real-time data processing, earning recognition for translating complex AI models into practical agricultural tools. His work is widely cited by interdisciplinary teams, reflecting its impact on both academic theory and field deployment. For students and researchers, Wu exemplifies how deep learning and robotics can address real-world challenges, making him a key figure in the growing field of smart agriculture.
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