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For the Inventor, By the Inventor

Zhejiang, China

Wei Hua

This inventor holds 9 USPTO granted patents and 4 published patent applications. Top assignee: Zhejiang Lab. Active years: 2022-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Wei Hua. Retrieved from https://idiyas.com/inventor/wei-hua-ue08xrp6

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 9 

% Patents Active = 100.0

Average Co-Inventor Count = 3.8

ph-index = 1

Forward Citations = 5(Granted Patents)


Location History:

  • Zhejiang, CN (2022)
  • Hangzhou, CN (2023 - 2024)

Company Filing History:

goldMedal9 out of 183 
 
Zhejiang Lab
 patents

Years Active: 2022-2025

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9 patents (USPTO):Explore Patents
1. 12346326 - Point cloud matching method and apparatus, electronic apparatus, and storage medium (2025-07-01),
2. 12117829 - Autonomous vehicle remote control apparatus and method based on heterogeneous networks (2024-10-15),
3. 11941532 - Method for adapting deep learning framework to hardware device based on unified backend engine (2024-03-26),
4. 11900618 - System and method for detecting moving target based on multi-frame point cloud (2024-02-13),
5. 11868869 - Non-intrusive load monitoring method and device based on temporal attention mechanism (2024-01-09),
6. 11836966 - Efficient across-camera target re-identification method based on similarity (2023-12-05),
7. 11823053 - Method of neural network model computation-oriented intermediate representation by constructing physical computation graph, inferring information of input and output tensor edges of each node therein, performing memory optimization on tensor edges, and optimizing physical computation graph (2023-11-21),
8. 11714995 - Method for distributed type training adaptation and apparatus in deep learning framework and AI accelerator card (2023-08-01),
9. 11436494 - Optimal power flow computation method based on multi-task deep learning (2022-09-06),

Title: Wei Hua - Innovator in Point Cloud Technology and Autonomous Vehicles

Introduction

Wei Hua is a prominent inventor based in Zhejiang, China. He has made significant contributions to the fields of point cloud technology and autonomous vehicle systems. With a total of 9 patents, his work is at the forefront of innovation in these areas.

Latest Patents

Wei Hua's latest patents include a point cloud matching method and apparatus, as well as an autonomous vehicle remote control apparatus and method based on heterogeneous networks. The point cloud matching method involves dividing a to-be-matched point cloud into multiple matched point cloud patches. These patches are then processed through a pre-trained point cloud feature coding module to obtain feature vectors. The global description vector of the to-be-matched point cloud is matched with global description vectors from a historical database to determine the best matching result.

His autonomous vehicle remote control apparatus enhances the reliability of remote control by avoiding areas with poor network quality. This innovation utilizes heterogeneous network resources effectively, improving the real-time performance of vehicle information acquisition and ensuring safer vehicle operation.

Career Highlights

Wei Hua is currently associated with Zhejiang Lab, where he continues to develop cutting-edge technologies. His work has garnered attention for its practical applications in both consumer and industrial sectors.

Collaborations

He collaborates with notable colleagues, including Hongsheng Wang and Hujun Bao, contributing to a dynamic research environment that fosters innovation.

Conclusion

Wei Hua's contributions to point cloud technology and autonomous vehicles exemplify the spirit of innovation. His patents reflect a commitment to enhancing technology for safer and more efficient systems.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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