Shenzhen, China

Zixun Sun


Average Co-Inventor Count = 2.3

ph-index = 1


Company Filing History:


Years Active: 2023-2024

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3 patents (USPTO):Explore Patents

Title: Zixun Sun: Innovator in Game Technology and Semantic Segmentation

Introduction

Zixun Sun is a prominent inventor based in Shenzhen, China. He has made significant contributions to the fields of game technology and semantic segmentation. With a total of 3 patents, his work showcases innovative methods that enhance user experience and improve machine learning processes.

Latest Patents

Zixun Sun's latest patents include a barrage generation method and apparatus, as well as a method and apparatus for generating training samples of a semantic segmentation model. The barrage generation method involves obtaining a target game video, determining barrage trigger information based on the video content, and generating barrage text at specific trigger times. This innovation aims to enhance the interactive experience in gaming environments. His second patent focuses on generating training samples for semantic segmentation models, which includes obtaining object identifiers and creating labeled images to improve the training process for machine learning applications.

Career Highlights

Zixun Sun is currently employed at Tencent Technology (Shenzhen) Company Limited, where he applies his expertise in technology and innovation. His work at Tencent has allowed him to contribute to cutting-edge projects that push the boundaries of gaming and artificial intelligence.

Collaborations

Zixun has collaborated with notable coworkers, including Zirui Tu and Chengwei Zhu. Their combined efforts have led to advancements in their respective fields, fostering a collaborative environment that encourages innovation.

Conclusion

Zixun Sun is a talented inventor whose work in barrage generation and semantic segmentation is paving the way for future advancements in technology. His contributions at Tencent Technology highlight the importance of innovation in enhancing user experiences and improving machine learning methodologies.

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