Beijing, China

Guoli Wang

USPTO Granted Patents = 2 

Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2022

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2 patents (USPTO):Explore Patents

Title: Guoli Wang: Innovator in Neural Network Technologies

Introduction

Guoli Wang, based in Beijing, China, is a distinguished inventor with a focus on advancing neural network technologies through innovative methods and devices. With a total of two patents to his name, Wang's contributions have significantly enhanced electronic devices and image recognition systems.

Latest Patents

Guoli Wang's latest patents include a **Method for Updating Neural Network and Electronic Device** and an **Image Recognition Method, Electronic Apparatus, and Readable Storage Medium**. The first patent outlines a method that involves inputting a first image set with tag information into a depth neural network to determine a cross-entropy loss value. Additionally, it incorporates a second image set without tags to update parameters across two neural networks, thereby optimizing performance. The second patent focuses on a sophisticated image recognition method that employs convolutional neural networks to align and fuse feature maps from current and key frame images for improved content recognition.

Career Highlights

Wang serves at Beijing Horizon Robotics Technology Research and Development Co., Ltd., where he harnesses his expertise in neural networks to drive the company's innovation agenda. His work is crucial in developing cutting-edge solutions that cater to the growing demand for advanced image recognition technologies.

Collaborations

Throughout his career, Guoli Wang has collaborated with influential colleagues such as Qian Zhang and Chang Huang. Their combined efforts foster an innovative environment that leads to groundbreaking advancements in robotics and artificial intelligence.

Conclusion

As an inventor, Guoli Wang continues to contribute to the field of technology with his innovative approaches to neural networks and image recognition. His patents reflect a commitment to enhancing the capabilities of electronic devices, thereby influencing the broader landscape of artificial intelligence and machine learning applications.

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