Hangzhou, China

Zixiao Wang


 

Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2020

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2 patents (USPTO):Explore Patents

Title: Zixiao Wang: Innovator in Automotive Damage Assessment Technology

Introduction

Zixiao Wang is a prominent inventor based in Hangzhou, China. He has made significant contributions to the field of automotive technology, particularly in the area of vehicle damage assessment. With a total of 2 patents, his work focuses on improving the accuracy and efficiency of automotive part recognition.

Latest Patents

Wang's latest patents include a method and apparatus for improving vehicle loss assessment image identification results. This innovation discloses systems and methods for automotive part recognition based on a vehicle damage assessment image. The method involves obtaining a damage assessment image of a target vehicle and an automotive part list based on the vehicle's identification code. It utilizes an image recognition algorithm to determine the damaged automotive part and obtain its identification serial number. Another patent details a similar method for recognizing damaged automotive parts, emphasizing the importance of matching the damaged part with a comprehensive automotive part list.

Career Highlights

Throughout his career, Zixiao Wang has worked with notable companies such as Alibaba Group Holding Limited and Advanced New Technologies Co., Ltd. His experience in these organizations has allowed him to develop and refine his innovative ideas in automotive technology.

Collaborations

Wang has collaborated with talented individuals in his field, including Guanru Li and Jian Jun Wang. These partnerships have contributed to the advancement of his projects and the successful development of his patents.

Conclusion

Zixiao Wang is a key figure in the automotive technology sector, with a focus on enhancing vehicle damage assessment through innovative methods and systems. His contributions are paving the way for more accurate automotive part recognition, which is essential for the industry.

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