Company Filing History:
Years Active: 2019
Title: Innovations of Jordan Donofrio in Handwriting Recognition
Introduction
Jordan Donofrio is an accomplished inventor based in Boston, MA, known for his innovative contributions to the field of handwriting recognition. He has developed a unique patent that leverages context-based machine learning to enhance the recognition of handwritten characters in digital images. His work is significant in the realm of digital data processing and user interaction.
Latest Patents
Jordan Donofrio holds a patent titled "Recognition of handwritten characters in digital images using context-based machine learning." This patent describes methods and apparatuses for recognizing handwritten characters in digital images. The process involves a server capturing an image of a document containing handwritten data fields associated with a user identifier. The server identifies the field type for each handwritten data field and creates a pixel intensity array for each character. If a user-specific character map exists, the server retrieves it to generate digital form data using a user-specific handwriting classifier. If no map exists, the server builds one based on the pixel intensity arrays and generates data using a baseline handwriting classifier.
Career Highlights
Jordan is currently employed at FMR Corp, where he applies his expertise in machine learning and handwriting recognition. His innovative approach has positioned him as a valuable asset in his field. He has successfully contributed to the development of technologies that improve the efficiency and accuracy of data entry processes.
Collaborations
Jordan collaborates with talented professionals such as Sunil Madhani and Fabrizio Machado. Their combined expertise fosters a creative environment that drives innovation and enhances project outcomes.
Conclusion
Jordan Donofrio's work in handwriting recognition exemplifies the intersection of technology and user experience. His patent showcases the potential of machine learning in transforming how handwritten data is processed and utilized. His contributions continue to influence advancements in the field, making a significant impact on digital data management.