Noida, India

Damandeep Singh Banga

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

IDiyas Innovation Intelligence. (2026). Inventor Profile: Damandeep Singh Banga. Retrieved from https://idiyas.com/inventor/damandeep-singh-banga

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

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Damandeep Singh Banga: Innovator in Book Page Boundary Detection

Introduction

Damandeep Singh Banga is a notable inventor based in Noida, India. He has made significant contributions to the field of image processing and machine learning. His innovative work focuses on enhancing the way physical books are digitized and interacted with.

Latest Patents

Banga holds a patent for "Precise book page boundary detection using deep machine learning model and image processing algorithms." This invention involves a method that utilizes a convolutional neural segmentation network to accurately detect the boundaries of book pages. The process generates outputs that define the left and right page boundaries of a physical book spread. By determining thin pixel masks and quadrilaterals for each page, the method allows for precise rendering of the page boundaries on a display.

Career Highlights

Damandeep Singh Banga is currently employed at Adobe Inc., where he continues to innovate in the realm of digital imaging and machine learning. His work at Adobe has allowed him to collaborate with other talented professionals in the industry, further enhancing his skills and contributions.

Collaborations

One of his notable coworkers is Tushar Tyagi, with whom he shares insights and expertise in their projects.

Conclusion

Damandeep Singh Banga's contributions to the field of book page boundary detection exemplify the intersection of technology and literature. His innovative patent showcases the potential of machine learning in transforming traditional reading experiences.

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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