Shanghai, China

Shi-Jie Chen


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2015-2016

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2 patents (USPTO):Explore Patents

Title: Innovations of Shi-Jie Chen

Introduction

Shi-Jie Chen is a notable inventor based in Shanghai, China. He has made significant contributions to the field of technology, particularly in language identification and handwriting recognition systems. With a total of 2 patents, his work showcases innovative approaches to solving complex problems in document processing and user interaction.

Latest Patents

One of Shi-Jie Chen's latest patents is titled "Method and apparatus for identifying a language used in a document and performing OCR recognition based on the language identified." This invention provides a method for identifying the language of a document based on the number of strokes per character. Once the language is identified, character recognition can occur using a tailored recognition engine specific to that language.

Another significant patent is the "Method and device for a multi-touch based correction of a handwriting sentence system." This invention involves receiving touch inputs to generate interpreted input data, which is then displayed on a device. The system allows users to enter correction mode, where gestures are used to determine the type of correction needed, enhancing the accuracy of handwriting recognition.

Career Highlights

Shi-Jie Chen has worked with prominent companies such as Motorola Solutions, Inc. and Symbol Technologies, LLC. His experience in these organizations has contributed to his expertise in developing innovative technologies.

Collaborations

Some of his notable coworkers include Qi-Zhen He and Ming-Xi Zhao, who have collaborated with him on various projects.

Conclusion

Shi-Jie Chen's contributions to technology through his patents reflect his innovative spirit and dedication to improving user interaction with technology. His work continues to influence advancements in language processing and handwriting recognition systems.

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