Shanfu Lu

Papers

Total Citations

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About

Shanfu Lu is a researcher at the intersection of artificial intelligence, robotics, and data science, with a primary focus on deep learning applications for autonomous systems. His most cited work, "Study on Technologies of Overhead Line Recognition and Obstacle Distance Measurement by Patrol Robots Based on Deep Learning" (2020), exemplifies his contributions to intelligent infrastructure inspection. In this study, Lu pioneered the integration of neural networks and feature extraction techniques to enable patrol robots to autonomously recognize overhead power lines and measure obstacle distances—a critical advancement for utility maintenance and safety. Though his citation count is currently modest (2 citations), the work demonstrates foundational innovation in combining computer vision with robotic navigation. Lu’s research spans broader domains including Big Data analytics, data mining, and educational technology, reflecting a versatile approach to solving real-world problems. His achievements highlight a commitment to applying deep learning in practical, high-impact settings, from autonomous robotics to data-driven decision-making. For students and researchers, Lu’s work offers a compelling example of how AI can transform traditional industries through precise, automated recognition and measurement systems.