Rochester, NY, United States of America

Stephen Ng


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):Explore Patents

Title: Innovations of Stephen Ng in Automated Detection Technologies.

Introduction

Stephen Ng is an accomplished inventor based in Rochester, NY (US). He has made significant contributions to the field of automated detection technologies, particularly in the analysis of structural changes through imagery. With a total of 3 patents, Ng's work showcases the intersection of machine learning and image processing.

Latest Patents

Ng's latest patents focus on systems and methods for automated detection of changes in the extent of structures using imagery. These patents include a non-transitory computer-readable medium that stores executable code. When executed by a processor, this code aligns an outline of a structure at a first instance of time with pixels within an image captured at a second instance of time. The system assesses the degree of alignment and classifies similarities using a machine learning model to generate an alignment confidence score. This score helps determine the existence of changes in the structure based on a predetermined threshold level of confidence.

Career Highlights

Stephen Ng is currently employed at Pictometry International Corporation, where he continues to innovate in the field of automated detection. His work has been instrumental in advancing technologies that enhance the accuracy and efficiency of structural assessments.

Collaborations

Ng collaborates with notable colleagues, including David R Nilosek and Phillip Salvaggio, who contribute to the innovative environment at Pictometry International Corporation.

Conclusion

Stephen Ng's contributions to automated detection technologies reflect his expertise and commitment to innovation. His patents are paving the way for advancements in structural analysis through imagery, showcasing the potential of machine learning in practical applications.

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