Boulder, CO, United States of America

Michelina Pallone

This inventor holds 1 USPTO granted patent. Top assignee: Google Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Michelina Pallone. Retrieved from https://idiyas.com/inventor/michelina-pallone

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

Calculating rank

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Michelina Pallone: Inventor Advancing Object Recognition from Overhead Imagery.

Introduction

Michelina Pallone is an inventor based in Boulder, Colorado, whose work includes machine-learning methods for identifying object boundaries in overhead imagery. She is associated with Google Inc. and is named on 1 patent.

Latest Patents

Pallone’s patent, “Object Outline Generation from Overhead Imagery Using Action Sequence Prediction,” describes a trained machine-learning model that identifies object boundaries in overhead images. The model is trained using overhead images paired with user-input actions. Given new imagery containing objects with unknown boundaries, it predicts sequences of actions associated with those boundaries, which are then used to determine the outlines.

Career Highlights

The patent reflects Pallone’s contribution to applying machine learning to image analysis. Its approach uses predicted action sequences to help identify the boundaries of multiple objects in overhead imagery.

Collaborations

Pallone’s listed company affiliation is Google Inc. The patent’s described method combines model training with user-action data to support object-boundary identification.

Conclusion

Michelina Pallone’s patented work applies action-sequence prediction to the challenge of outlining objects in overhead imagery.

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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