Beijing, China

Shimin Ruan

This inventor holds 1 USPTO granted patent. Top assignee: Beijing Baidu Netcom Science and Technology Co., Ltd.. Active years: 2021.


% Patents Active = 100.0

Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2021

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1 patent (USPTO):Explore Patents

Title: Shimin Ruan: Innovator in Deep Learning Model Conversion

Introduction

Shimin Ruan is a notable inventor based in Beijing, China. He has made significant contributions to the field of deep learning and model conversion. His innovative work has led to the development of a patent that enhances the applicability of existing models to target devices.

Latest Patents

Shimin Ruan holds a patent for a "Method and apparatus for generating model, method and apparatus for recognizing information." This patent describes a method that includes acquiring a to-be-converted model, a topology description of the model, and device information of a target device. The process involves converting parameters and operators of the model based on the topology description and device information to create a converted model. This model can then be used to generate a deep learning prediction model applicable to the target device. This innovation allows for the effective conversion of existing models into deep learning prediction models.

Career Highlights

Shimin Ruan is currently employed at Beijing Baidu Netcom Science and Technology Co., Ltd. His work at this leading technology company has positioned him at the forefront of advancements in artificial intelligence and machine learning.

Collaborations

Shimin has collaborated with several talented individuals in his field, including Yongkang Xie and En Shi, who is a woman. These collaborations have contributed to the success of his projects and the development of innovative technologies.

Conclusion

Shimin Ruan's contributions to the field of deep learning and model conversion are noteworthy. His patent reflects his commitment to advancing technology and improving the functionality of deep learning models. His work continues to influence the industry and inspire future innovations.

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