Warrenton, VA, United States of America

James Scrofani

This inventor holds 1 USPTO granted patent. Top assignee: USA as Represented by Secretary of the Navy. Active years: 2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: James Scrofani. Retrieved from https://idiyas.com/inventor/james-scrofani

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank

% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: James Scrofani: Innovator in Generative Adversarial Networks

Introduction

James Scrofani is an accomplished inventor based in Warrenton, VA (US). He has made significant contributions to the field of artificial intelligence, particularly in the area of generative adversarial networks (GANs). His innovative work focuses on enhancing the capabilities of machine learning models.

Latest Patents

James Scrofani holds a patent for an Extended Semi-Supervised Learning Generative Adversarial Network. This invention includes metrics for evaluating training performance and a method for generating an estimated label vector γ by the ESSL GAN discriminator. The embodiments of this invention improve classification accuracy over traditional convolutional neural networks, particularly with enhanced synthetic imagery.

Career Highlights

James Scrofani is currently associated with the United States Navy, where he contributes his expertise in advanced machine learning techniques. His work is pivotal in developing systems that leverage artificial intelligence for various applications.

Collaborations

James has collaborated with notable colleagues, including Andrew W. Hahn and Murali Tummala. Their combined efforts in research and development have furthered advancements in the field of generative adversarial networks.

Conclusion

James Scrofani's innovative contributions to generative adversarial networks exemplify the potential of artificial intelligence in improving classification accuracy. His work continues to influence the landscape of machine learning and its applications.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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