Mysuru, India

Pavan Narasimha Murthy

This inventor holds 1 USPTO granted patent and 3 published patent applications. Top assignee: L&t Technology Services Limited. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Pavan Narasimha Murthy. Retrieved from https://idiyas.com/inventor/pavan-narasimha-murthy

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

Calculating rank
USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Pavan Narasimha Murthy: Inventor of a Digital Label Comparison System.

Introduction

Pavan Narasimha Murthy is an inventor based in Mysuru, India. He works at L&T Technology Services Limited and is named on 1 patent.

Latest Patents

Murthy’s patent, “Method and System of Comparing Digital Labels,” describes a system for comparing two or more digital labels. A machine-learning or deep-learning model identifies regions of interest corresponding to objects in each label and classifies those objects as text or non-text.

For text objects, the system extracts attribute key-value pairs and compares the corresponding text data across labels. For non-text objects, it assigns each object to a category and can compare the associated regions of interest. The approach is designed to support structured comparison of both textual and visual label content.

Career Highlights

Murthy’s listed invention applies machine learning and deep learning to digital label analysis. His work at L&T Technology Services Limited provides the professional context for this patent.

Collaborations

Pragyesh Kumar and Tarun Kumar Das are identified as Murthy’s coworkers. The available information does not specify their roles in the patent or whether they collaborated on the invention.

Conclusion

Pavan Narasimha Murthy’s patent presents a method for comparing digital labels by analyzing their text and non-text elements, reflecting an application of machine learning to document and label processing.

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]
Loading…