Beijing, China

Guangqi Shao


Average Co-Inventor Count = 6.4

ph-index = 2

Forward Citations = 11(Granted Patents)


Company Filing History:


Years Active: 2018-2024

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3 patents (USPTO):Explore Patents

Title: Guangqi Shao: Innovator in Image Processing and Object Recognition

Introduction

Guangqi Shao is a prominent inventor based in Beijing, China. He has made significant contributions to the fields of image processing and object recognition. With a total of 3 patents, his work showcases innovative methods that enhance the way we interact with visual data.

Latest Patents

One of Guangqi Shao's latest patents is titled "Method for processing image, related device and storage medium." This method involves obtaining a media image that contains a target scene object that is at least partially shielded. The process includes determining a target shielding object from the media image, which shields the target scene object. Image inpainting is then performed on the region corresponding to the target shielding object to generate a target media image. Another notable patent is the "Object recognition method and apparatus." This invention provides an object recognition method that generates an input image based on an event flow of an object. It also includes generating a composite feature based on features extracted by multiple recognizers, ultimately recognizing the object based on this composite feature.

Career Highlights

Guangqi Shao has worked with leading technology companies, including Samsung Electronics and Xiaomi Mobile Software. His experience in these organizations has allowed him to refine his skills and contribute to cutting-edge projects in the tech industry.

Collaborations

Throughout his career, Guangqi has collaborated with talented individuals such as Xiaotao Wang and Wentao Mao. These partnerships have fostered innovation and creativity in his work.

Conclusion

Guangqi Shao's contributions to image processing and object recognition highlight his role as a key innovator in technology. His patents reflect a commitment to advancing the field and improving how we process and recognize visual information.

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