Zhengzhou, China

Jianchen Luo


Average Co-Inventor Count = 6.0

ph-index = 1


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Innovations by Jianchen Luo in Vehicle Speed Measurement

Introduction

Jianchen Luo is a notable inventor based in Zhengzhou, China. He has made significant contributions to the field of intelligent transportation systems. His innovative approach focuses on enhancing vehicle speed measurement through advanced technology.

Latest Patents

One of Jianchen Luo's key patents is titled "Vehicle speed intelligent measurement method based on binocular stereo vision system." This invention outlines a method for intelligently measuring vehicle speed using a binocular stereo vision system. The process involves training a Single Shot Multibox Detector neural network to create a license plate recognition model. It also includes calibrating the binocular stereo vision system to acquire parameters from two cameras. The system detects license plates in captured video frames, locates their positions, and performs feature point extraction and stereo matching. The invention is designed to be easy to install and adjust, allowing for the simultaneous recognition of multiple trained features. This makes it particularly suitable for intelligent transportation networks and the Internet of Things (IoT).

Career Highlights

Jianchen Luo has achieved recognition for his innovative work in the field of vehicle speed measurement. His patent demonstrates a blend of machine learning and stereo vision technology, showcasing his expertise in integrating advanced systems for practical applications.

Collaborations

Jianchen has collaborated with notable colleagues, including Lei Yang and Xiaowei Song, to further enhance the development of his inventions. Their combined efforts have contributed to the advancement of intelligent transportation solutions.

Conclusion

Jianchen Luo's contributions to vehicle speed measurement through his innovative patent highlight the potential of technology in improving transportation systems. His work exemplifies the intersection of machine learning and practical applications in the field of intelligent transportation.

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