Cranberry Township, PA, United States of America

Michael Joseph Rondinelli

This inventor holds 1 USPTO granted patent. Top assignee: Ford Global Technolgoies, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Michael Joseph Rondinelli. Retrieved from https://idiyas.com/inventor/michael-joseph-rondinelli

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


% Patents Active = 100.0

Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Michael Joseph Rondinelli and Video Annotation for Machine Learning.

Introduction

Michael Joseph Rondinelli is an inventor associated with Cranberry Township, Pennsylvania, United States. His patent work addresses the preparation of video data for training machine-learning systems.

Latest Patents

Rondinelli is credited with 1 patent. The patent, titled “Neural network,” describes a computer with a processor and memory configured to plot three-dimensional positions of labeled cuboids across frames between two keyframes in a densely labeled video sequence. It also describes generating a sparsely labeled sequence by removing cuboids whose positions fall within a user-selected distance of a line connecting their positions in the keyframes. The resulting sequence can be provided as training data for a machine-learning system.

Career Highlights

Rondinelli is associated with Ford Global Technologies, LLC. His patent reflects work on streamlining video annotation by using keyframe positions to help create training data.

Collaborations

The supplied information identifies Rose Amalia Ciriello and Dave Chekan as coworkers. It does not specify their roles in the patent or describe particular joint projects.

Conclusion

Michael Joseph Rondinelli’s patent focuses on generating sparsely labeled video sequences from densely annotated footage, supporting the preparation of data for machine-learning training.

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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