Company Filing History:
Years Active: 2019
Title: Innovations of Christopher A McDermott
Introduction
Christopher A McDermott is an accomplished inventor based in Barrington, RI (US). He has made significant contributions to the field of machine learning, particularly in the recognition of handwritten characters in digital images. His innovative approach combines technology with practical applications, enhancing the way handwritten data is processed.
Latest Patents
Christopher A McDermott holds a patent for the invention 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
Christopher is currently employed at FMR Corp., where he applies his expertise in machine learning and data processing. His work has contributed to advancements in the recognition of handwritten data, making it easier for users to digitize and manage their information.
Collaborations
Some of Christopher's notable coworkers include Sunil Madhani and Fabrizio Machado. Their collaboration has likely fostered an environment of innovation and creativity, leading to further advancements in their respective fields.
Conclusion
Christopher A McDermott's contributions to the field of machine learning and handwritten character recognition demonstrate his commitment to innovation. His patent reflects a significant advancement in technology that enhances the efficiency of data processing.