Kapurthala, India

Nitin Rathor


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 14(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Nitin Rathor: Innovator in Makeup Identification Technology

Introduction

Nitin Rathor is a notable inventor based in Kapurthala, India. He has made significant contributions to the field of digital makeup identification through his innovative patent. His work focuses on utilizing deep learning techniques to enhance the way makeup characteristics are identified and described in digital images.

Latest Patents

Nitin Rathor holds a patent for "Makeup identification using deep learning." This patent describes a method for identifying makeup characteristics in a digital medium environment. The process begins with receiving a digital image of a face that exhibits a desired makeup characteristic. A discriminative neural network is then trained to analyze the input image, comparing it with another image that depicts a face without makeup. The neural network identifies and describes the makeup characteristics, which are then displayed for user selection. This allows users to search for similar digital images that share the selected makeup characteristic.

Career Highlights

Nitin Rathor is currently employed at Adobe Inc., where he applies his expertise in deep learning and image processing. His work at Adobe has allowed him to contribute to advancements in digital media and technology. With a patent portfolio that includes 1 patent, he continues to push the boundaries of innovation in his field.

Collaborations

Nitin collaborates with talented coworkers, including Niyati Himanshu Chhaya and Lilly Kumari. Their combined efforts contribute to the development of cutting-edge technologies at Adobe.

Conclusion

Nitin Rathor's innovative work in makeup identification using deep learning showcases his commitment to advancing technology in the digital space. His contributions are paving the way for new possibilities in how makeup characteristics are recognized and utilized in digital media.

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