Santa Clara, CA, United States of America

Yu Sun


Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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2 patents (USPTO):Explore Patents

Title: Innovations of Yu Sun in Machine Learning for Driving Systems

Introduction

Yu Sun is an accomplished inventor based in Santa Clara, CA. He has made significant contributions to the field of machine learning, particularly in developing methods for enhancing driving systems. His innovative approach combines various technologies to improve the classification of environmental scenarios for vehicles.

Latest Patents

Yu Sun holds a patent titled "Methods and apparatus for natural language based scenario discovery to train a machine learning model for a driving system." This patent presents a method for classifying environmental image frames for vehicles using a universal iterative classification model. The method integrates text-based querying, active machine-learning models, and user input to create an end-to-end automatic flow for sourcing video frames captured by vehicle sensors. An index of frames is continuously populated with new data, scoring each frame based on its likelihood of representing a driving scenario of interest. The iterative classification model produces results that can be labeled and refined through subsequent training, enhancing precision and accuracy in classifying image data.

Career Highlights

Yu Sun is currently associated with Plusai Limited, where he applies his expertise in machine learning to develop innovative solutions for driving systems. His work focuses on improving the interaction between vehicles and their environments through advanced classification techniques.

Collaborations

Yu collaborates with talented individuals such as Yang Yang and Anurag Paul, contributing to a dynamic team that drives innovation in their field.

Conclusion

Yu Sun's contributions to machine learning and driving systems exemplify the impact of innovative thinking in technology. His patent and ongoing work at Plusai Limited highlight the importance of advancements in this critical area.

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