New York, NY, United States of America

Houssem Chatbri

USPTO Granted Patents = 1 

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Houssem Chatbri: Innovator in Handwriting Extraction Technology

Introduction

Houssem Chatbri is an accomplished inventor based in New York, NY (US). He has made significant contributions to the field of machine learning, particularly in the area of handwriting extraction from images. His innovative approach has the potential to enhance the way handwritten content is recognized and processed.

Latest Patents

Houssem Chatbri holds a patent for "Methods and systems for adaptive, template-independent handwriting extraction from images using machine learning models." This patent describes a system that can receive an input image containing both native printed content and handwritten content. The system processes the input image with a model to generate an output image that includes extracted handwritten content. Furthermore, it digitally recognizes the extracted handwritten content and generates a digital representation of the input image, which comprises both the native printed content and the digitally recognized handwritten content. This technology represents a significant advancement in the field of image processing and machine learning.

Career Highlights

Houssem Chatbri is currently employed at The Bank of New York Mellon Corporation, where he applies his expertise in machine learning and image processing. His work at the bank allows him to explore innovative solutions that can improve operational efficiency and enhance customer experiences.

Collaborations

Houssem collaborates with talented professionals in his field, including his coworker Bethany Kok. Their combined efforts contribute to the development of cutting-edge technologies that push the boundaries of what is possible in handwriting recognition.

Conclusion

Houssem Chatbri is a notable inventor whose work in handwriting extraction technology showcases the intersection of machine learning and practical applications. His contributions are paving the way for advancements in how handwritten content is processed and recognized in various industries.

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