Beijing, China

Libo Fu


Average Co-Inventor Count = 2.5

ph-index = 2

Forward Citations = 10(Granted Patents)


Company Filing History:


Years Active: 2019-2022

where 'Filed Patents' based on already Granted Patents

4 patents (USPTO):

Title: Innovator Libo Fu: Advancing Training Data Acquisition Methods in Beijing

Introduction: Libo Fu, an accomplished inventor based in Beijing, China, is known for his significant contributions to the field of training data acquisition. With a total of four patents to his name, Fu's work focuses on enhancing the performance of classifiers through innovative methods.

Latest Patents: Among his recent inventions, Fu has developed a groundbreaking training data acquisition method and device, along with a server and storage medium. This method is designed for application to classifiers and includes a series of steps aimed at optimizing the acquisition of high-quality training data. The process involves obtaining an image search target based on user input, displaying corresponding images, and selecting at least one image to form a target-classification pair. This pair comprises the image search target and an entity-based classification of the selected image, which collectively improve classifier performance.

Career Highlights: Libo Fu has made his mark as a vital member of Baidu Online Network Technology (Beijing) Co., Ltd., where he leverages his expertise in creating innovative solutions that enhance data processing and machine learning capabilities. His commitment to innovation in technology has positioned him as a notable figure within the industry.

Collaborations: Fu collaborates with talented professionals, including Gaolin Fang and Su Li, who bring together diverse skills and perspectives to foster groundbreaking developments in technology. The synergy among this dynamic team contributes to the success of their projects, particularly in the realm of machine learning and data acquisition.

Conclusion: Libo Fu's inventive spirit and dedication to enhancing training data acquisition methods are paving the way for future advancements in the field. With a focus on improving classifier performance, Fu's work not only showcases his innovative capabilities but also highlights the collaborative efforts of professionals striving to push the boundaries of technology in Beijing.

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