Shengzan Yan

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About

Shengzan Yan is a researcher at the forefront of computer vision and intelligent robotics, with a focus on human–computer interaction and sustainable energy technologies. His work bridges the gap between advanced algorithmic design and practical engineering solutions. Yan’s most cited paper, “Motion Recognition Algorithm Based on Deep Edge-Aware Pyramid Pooling Network in Human–Computer Interaction” (2019, 14 citations), introduces a novel deep learning architecture that enhances action recognition accuracy in complex, multi-angle environments—a critical contribution for applications in video surveillance and human-robot interaction. Building on this expertise, Yan also addresses real-world challenges in renewable energy with his paper “Research on Design of Intelligent Cleaning Robot for Solar Panel” (2020, 6 citations), proposing an automated cleaning system to maintain efficiency in desert-based solar farms. By combining deep edge-aware pooling networks with robotic design, Yan demonstrates a unique ability to translate theoretical computer vision advances into deployable technologies. His work not only advances algorithmic robustness but also supports the growing demand for sustainable infrastructure, making him a notable figure in applied AI and robotics research.