Jiangmen, China

Yueting Wu

USPTO Granted Patents = 2 

Average Co-Inventor Count = 9.0

ph-index = 1


Company Filing History:


Years Active: 2021-2023

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2 patents (USPTO):Explore Patents

Title: Innovations by Yueting Wu in Antenna Technology

Introduction

Yueting Wu is a notable inventor based in Jiangmen, China, recognized for his contributions to antenna technology. With a total of two patents, Wu has developed innovative methods that enhance the measurement of antenna downtilt angles, utilizing advanced deep learning techniques.

Latest Patents

Wu's latest patents include a "Method for measuring antenna downtilt angle based on multi-scale deep semantic segmentation network." This method involves collecting base station antenna data using an unmanned aerial vehicle and labeling the acquired antenna images to create a dataset. The dataset is then used for training and debugging a model that recognizes and detects target antennas, performing semantic segmentation to calculate the downtilt angle accurately. This method is noted for its high applicability, cost-effectiveness, and safety.

Another significant patent is the "Method for measuring antenna downtilt angle based on deep instance segmentation network." This method utilizes a drone to capture omni-directional antenna videos, which are transmitted to a server in real time. The server employs a deep learning algorithm to measure the antenna downtilt angle, featuring modules for feature extraction, instance segmentation, and candidate box identification, culminating in precise angle measurement.

Career Highlights

Yueting Wu is affiliated with Wuyi University, where he continues to advance research in antenna technology. His work has significantly impacted the field, particularly in the application of deep learning for real-time measurements.

Collaborations

Wu collaborates with colleagues such as Yikui Zhai and Jihua Zhou, contributing to a dynamic research environment that fosters innovation in antenna technology.

Conclusion

Yueting Wu's innovative methods for measuring antenna downtilt angles represent a significant advancement in the field, showcasing the potential of deep learning in practical applications. His contributions continue to influence the development of efficient and effective antenna measurement techniques.

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