Sunnyvale, CA, United States of America

Adrien Delaye

USPTO Granted Patents = 3 

Average Co-Inventor Count = 5.1

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2020-2024

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3 patents (USPTO):

Title: Innovations by Adrien Delaye

Introduction

Adrien Delaye is an accomplished inventor based in Sunnyvale, CA. He has made significant contributions to the field of handwriting input technology, holding a total of three patents. His work focuses on enhancing the user experience in digital handwriting recognition and control.

Latest Patents

One of Adrien's latest patents is titled "Stroke based control of handwriting input." This technology provides a method for stroke-based control that facilitates various operations for handwritten electronic text, such as selection, copy, paste, and search. The innovation allows users to select text represented by handwritten strokes without the need for drawing a lasso around the desired text. Instead, it utilizes known boundaries of words and phrases in stroke space, enabling efficient text manipulation. Another notable patent is "Handwritten text recognition," which involves receiving a new input stroke and determining its association with an existing line group based on writing direction. This technology merges the new stroke with the existing line group, enhancing the accuracy of handwritten text recognition.

Career Highlights

Adrien Delaye is currently employed at Apple Inc., where he continues to develop innovative technologies that improve handwriting input systems. His work has been instrumental in advancing the capabilities of digital handwriting recognition, making it more intuitive and user-friendly.

Collaborations

Adrien collaborates with talented individuals such as Ryan S Dixon and Dominic L Howell, contributing to a dynamic team focused on innovation in technology.

Conclusion

Adrien Delaye's contributions to handwriting input technology exemplify the impact of innovation in enhancing user interaction with digital devices. His patents reflect a commitment to improving the efficiency and functionality of handwriting recognition systems.

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