Rongzhi Qi

Title: Rongzhi Qi: Innovator in Dam Defect Recognition Technology

Introduction

Rongzhi Qi is a notable inventor based in Yunnan, China. He has made significant contributions to the field of intelligent recognition methods for concrete dam defects. With a total of 3 patents, his work focuses on enhancing the accuracy and efficiency of defect detection in dam structures.

Latest Patents

Rongzhi Qi's latest patents include an "Intelligent recognition method for time sequence image of concrete dam defect." This innovative method involves extracting a feature sequence from time sequence images containing concrete dam defects. It matches located defects with real defects using an objective function and incorporates a loss term to improve accuracy. The method effectively detects defects in long image sequences, allowing for precise recognition of defect types.

Another significant patent is the "Time-series image description method for dam defects based on local self-attention." This method utilizes frame sampling on input time-series images and employs a convolutional neural network to extract feature sequences. It integrates a self-attention encoder, which includes a Transformer network that dynamically establishes contextual feature relations for each frame. The method enhances text generation accuracy by establishing a contextual dependency between image and text.

Career Highlights

Rongzhi Qi has worked with esteemed organizations such as Hohai University and Huaneng Lanceng River Hydropower Inc. His experience in these institutions has contributed to his expertise in dam defect recognition technology.

Collaborations

Rongzhi Qi has collaborated with notable colleagues, including Hongqi Ma and Yingchi Mao. Their joint efforts have further advanced the field of intelligent recognition methods.

Conclusion

Rongzhi Qi's innovative work in dam defect recognition technology showcases his commitment to improving safety and efficiency in civil engineering. His patents reflect a deep understanding of the challenges in this field and offer practical solutions for defect detection.