Yunnan, China

Rui Guo


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: The Innovative Contributions of Rui Guo

Introduction

Rui Guo is a prominent inventor based in Yunnan, China. He has made significant strides in the field of image processing, particularly in the context of concrete dam defect analysis. His innovative approach combines advanced neural network techniques with practical applications in engineering.

Latest Patents

Rui Guo holds a patent for an "Automatic concrete dam defect image description generation method based on graph attention network." This invention involves several key steps: first, it extracts local grid features and whole image features from defect images using a multi-layer convolutional neural network. Next, it constructs a grid feature interaction graph to fuse and encode these features. The method then updates and optimizes both global and local features through a graph attention network, allowing for improved visual feature utilization in defect descriptions. This invention effectively captures global image information and local feature interactions, resulting in accurate and coherent defect information descriptions.

Career Highlights

Throughout his career, Rui Guo has worked with notable organizations, including Huaneng Lancang River Hydropower Inc. and Hohai University. His experience in these institutions has contributed to his expertise in engineering and image processing technologies.

Collaborations

Rui Guo has collaborated with several professionals in his field, including Hua Zhou and Fudong Chi. These partnerships have likely enhanced his research and development efforts, leading to innovative solutions in his area of expertise.

Conclusion

Rui Guo's contributions to the field of image processing and defect analysis demonstrate his innovative spirit and technical prowess. His patent reflects a significant advancement in the automatic generation of defect descriptions, showcasing the potential of combining neural networks with practical engineering applications.

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