Yuxi Yang
Papers
1
Total Citations
1
H-Index
1
About
Yuxi Yang is a researcher focused on the intersection of computer vision and renewable energy infrastructure, with a particular emphasis on automated defect detection in photovoltaic systems. Their most notable contribution is the development of an enhanced YOLOv9 algorithm, specifically designed to identify stains and physical damage on solar panels. This work addresses a critical challenge in solar energy maintenance: the need for rapid, accurate, and cost-effective inspection of large-scale photovoltaic arrays. By refining the state-of-the-art YOLOv9 object detection framework, Yang’s algorithm improves detection precision and speed, enabling real-time monitoring that can prevent energy loss and extend panel lifespan. The study, published in 2025, has already garnered early citations, signaling its relevance to both the computer vision and solar energy communities. Yang’s research bridges deep learning with practical engineering applications, offering a scalable solution for the growing solar industry. Their work is particularly valuable for researchers and engineers seeking to integrate AI-driven diagnostics into renewable energy systems, demonstrating how advanced algorithms can directly support sustainability goals.
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