Beijing, China

Guoxing Li


Average Co-Inventor Count = 2.0

ph-index = 2

Forward Citations = 9(Granted Patents)


Company Filing History:


Years Active: 2002-2007

Loading Chart...
7 patents (USPTO):Explore Patents

Title: Guoxing Li: Innovator in Handwriting Recognition Technology

Introduction

Guoxing Li is a prominent inventor based in Beijing, China, known for his significant contributions to handwriting recognition technology. With a total of seven patents to his name, Li has developed innovative methods and systems that enhance the accuracy and efficiency of recognizing handwritten characters.

Latest Patents

One of his latest patents is focused on unconstrained handwriting recognition. This invention includes methods and systems that utilize digital image data arranged in rows and columns. The exemplary embodiments feature a feature extractor that extracts information from the digital image data, a feature compressor that compresses this information, and a neural network that classifies the data based on the compressed features. Another notable patent is the VLSI neural fuzzy classifier for handwriting recognition. This device employs fuzzy logic and cellular neural networks to classify unconstrained handwritten numerals. It includes an I/O circuit for inputting and outputting multiple membership functions, an extraction unit with a CCD extractor, and a compression unit that generates feature values for recognition.

Career Highlights

Throughout his career, Guoxing Li has worked with notable companies such as Winbond Electronics Corporation and Windbond Electronics Corp. His experience in these organizations has contributed to his expertise in developing advanced technologies in the field of handwriting recognition.

Collaborations

Li has collaborated with various professionals in his field, including Bingxue Shi, enhancing the development of innovative solutions in handwriting recognition.

Conclusion

Guoxing Li's work in handwriting recognition technology showcases his dedication to innovation and excellence. His patents reflect a deep understanding of the complexities involved in recognizing handwritten characters, making significant strides in this area of technology.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to support@idiyas.com
Loading…