Moscow, Russia

Vladimir Rybkin

USPTO Granted Patents = 17 

Average Co-Inventor Count = 2.4

ph-index = 3

Forward Citations = 36(Granted Patents)


Company Filing History:


Years Active: 2006-2021

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17 patents (USPTO):Explore Patents

Title: Inventor Vladimir Rybkin: Innovating Optical Character Recognition Technologies

Introduction

Vladimir Rybkin is a notable inventor based in Moscow, Russia, with an impressive portfolio of 17 patents to his name. His work primarily focuses on advancements in optical character recognition (OCR) technologies, aimed at improving the accuracy and efficiency of text recognition in various applications.

Latest Patents

Among his latest patents, Rybkin's work includes a method for differential classification using multiple neural networks. This patent describes a classification engine that generates sets of confused graphemes based on recognition data, identifying neural networks trained for specific recognition tasks. Another significant patent is the method and system for preparing text images for optical character recognition. This innovation involves correcting text images with curved lines, ensuring that characters are presented in a straightened and organized manner for improved recognition.

Career Highlights

Rybkin has had a significant impact on the field of OCR through his innovations. He has worked with prominent companies such as Abbyy Software Limited and Abbyy Development Inc., where his expertise in developing cutting-edge OCR technologies has been instrumental in enhancing their product offerings.

Collaborations

Throughout his career, Rybkin has collaborated with talented professionals, including Konstantin Anisimovich and Olga Arnoldova Kacher. These partnerships have contributed to the development and implementation of innovative solutions in the field of OCR.

Conclusion

Vladimir Rybkin's contributions to optical character recognition technology are noteworthy, with several patents highlighting his dedication and innovation in the field. His collaborations and career achievements continue to influence advancements in text recognition, showcasing the importance of his work in improving digital text processing.

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