Stanford, CA, United States of America

Iro Armeni


Average Co-Inventor Count = 5.0

ph-index = 2

Forward Citations = 11(Granted Patents)


Company Filing History:


Years Active: 2019-2021

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2 patents (USPTO):Explore Patents

Title: Iro Armeni: Innovator in 3D Semantic Segmentation

Introduction

Iro Armeni is a notable inventor based in Stanford, CA, who has made significant contributions to the field of 3D point cloud processing. With a total of 2 patents, Armeni's work focuses on advanced systems and methods for semantic segmentation and parsing of three-dimensional spaces. His innovative approaches have the potential to enhance various applications in computer vision and spatial analysis.

Latest Patents

Armeni's latest patents include "Systems and methods for semantic segmentation of 3D point clouds" and "Systems and methods for performing three-dimensional semantic parsing of indoor spaces." The first patent outlines a method that involves pre-processing a 3D point cloud to group points, utilizing a 3D neural network for initial label predictions, and refining these predictions through a graph neural network. The second patent describes a method for analyzing three-dimensional spaces by determining disjointed areas and generating detection scores for elements within those spaces.

Career Highlights

Iro Armeni is affiliated with Leland Stanford Junior University, where he continues to push the boundaries of research in 3D technology. His work is characterized by a strong emphasis on practical applications and innovative methodologies that address complex challenges in the field.

Collaborations

Armeni collaborates with esteemed colleagues such as Silvio Savarese and Lyne P Tchapmi, contributing to a dynamic research environment that fosters innovation and discovery.

Conclusion

Iro Armeni's contributions to the field of 3D point cloud processing exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing the understanding and application of semantic segmentation and parsing in three-dimensional spaces.

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