West Bengal, India

Pradip Gupta

This inventor holds 1 USPTO granted patent. Top assignee: Jio Platforms Limited. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Pradip Gupta. Retrieved from https://idiyas.com/inventor/pradip-gupta-xe4hf8i9

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


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Pradip Gupta and Automated Object Footprint Detection.

Introduction

Pradip Gupta is an inventor associated with West Bengal, India, and Jio Platforms Limited. His patent work focuses on automating the analysis of imagery to identify objects and generate their footprint vectors.

Latest Patents

Gupta is credited with 1 patent: “Automated Imaging System for Object Footprint Detection and a Method Thereof.” The invention describes a system that can retrieve imagery of a specified location from a mapping module and identify multiple objects within it. A deep-learning-based segmentation method, including a cascaded reverse Mask R-CNN framework, can then generate predefined vectors associated with the image. The system is designed to automate vector generation using imagery received from an image-sensing assembly.

Career Highlights

Gupta’s listed patent reflects work at the intersection of image processing, deep learning, and automated mapping analysis. He is associated with Jio Platforms Limited.

Collaborations

The available information identifies Jio Platforms Limited as Gupta’s company affiliation. It does not specify additional collaborators or research partners for the patent.

Conclusion

Pradip Gupta’s patent describes an automated approach to extracting objects from location imagery and generating their associated footprint vectors.

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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