Cailing Tang

Title: Cailing Tang: Innovator in Tunnel Dome Light Detection

Introduction

Cailing Tang is a prominent inventor based in Nanchang, China. He has made significant contributions to the field of fault detection methods, particularly in the context of tunnel dome lights. His innovative approach utilizes advanced neural network techniques to enhance the reliability and efficiency of tunnel lighting systems.

Latest Patents

Cailing Tang holds a patent for a "Fault detection method and system for tunnel dome lights based on improved localization loss function." This patent describes a method that includes constructing a dataset of tunnel dome light detection images. It involves acquiring a YOLO v5s neural network based on the improved localization loss function. The process includes training the YOLO v5s neural network with the dataset to obtain a trained model. The trained network is then used to detect tunnel dome light images, providing position coordinates of luminous dome lights. This method allows for accurate localization and labeling of tunnel dome lights, enabling the detection of faults based on their positional relationships.

Career Highlights

Cailing Tang is affiliated with East China Jiaotong University, where he contributes to research and development in innovative technologies. His work focuses on enhancing safety and operational efficiency in tunnel lighting systems through advanced detection methods.

Collaborations

Cailing Tang collaborates with notable colleagues, including Gang Yang and Lizhen Dai. Their combined expertise fosters a productive research environment that drives innovation in their respective fields.

Conclusion

Cailing Tang's contributions to the field of fault detection in tunnel dome lights exemplify the impact of innovative thinking in engineering. His work not only advances technology but also enhances safety in tunnel operations.