Redwood City, CA, United States of America

Lianghao Li

USPTO Granted Patents = 5 

Average Co-Inventor Count = 3.2

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2021-2023

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5 patents (USPTO):Explore Patents

Title: Innovations by Inventor Lianghao Li

Introduction

Lianghao Li is an accomplished inventor based in Redwood City, CA. He has made significant contributions to the field of machine learning and agricultural technology. With a total of 5 patents, his work focuses on generating synthetic training data for plant disease detection and other related applications.

Latest Patents

Li's latest patents include innovative methods for generating and using synthetic training data for plant disease detection. These implementations involve automatically creating synthetic training images that can be utilized for training machine learning models to detect and classify various types of plant diseases. The process includes retrieving environmental features associated with agricultural areas and generating synthetic plant models that visually simulate different stages of plant diseases. Another notable patent focuses on generating quasi-realistic synthetic training data for machine learning models to perceive various plant traits. This involves creating labeled simulated images that depict instances of plants with targeted traits, enhancing the training process for machine learning applications.

Career Highlights

Throughout his career, Lianghao Li has worked with notable companies such as X Development LLC and Mineral Earth Sciences LLC. His experience in these organizations has allowed him to develop and refine his innovative ideas in the realm of agricultural technology and machine learning.

Collaborations

Li has collaborated with talented individuals in his field, including Kangkang Wang and Zhiqiang Yuan. These partnerships have contributed to the advancement of his research and the successful implementation of his inventions.

Conclusion

Lianghao Li's contributions to the field of machine learning and agricultural technology are noteworthy. His innovative patents and collaborations reflect his commitment to advancing technology for plant disease detection and trait analysis.

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