La Jolla, CA, United States of America

Aman Raj


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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2 patents (USPTO):Explore Patents

Title: Innovations of Aman Raj in Computer Vision

Introduction

Aman Raj is an accomplished inventor based in La Jolla, California. He has made significant contributions to the field of computer vision through his innovative patents. With a total of two patents to his name, Aman is recognized for his expertise in deep machine learning applications.

Latest Patents

Aman's latest patents focus on a system and method for deep machine learning for computer vision applications. This computer vision training system includes a supervised learning system that estimates a supervision output from one or more input images according to a target computer vision application. It also determines a supervised loss based on the supervision output and a ground-truth of the supervision output. Additionally, the system features an unsupervised learning system that calculates an unsupervised loss based on the supervision output and the input images. Furthermore, a weakly supervised learning system is included to determine a weakly supervised loss corresponding to the input images. A joint optimizer is employed to concurrently optimize the supervised loss, unsupervised loss, and weakly supervised loss.

Career Highlights

Aman Raj is currently employed at Samsung Electronics Co., Ltd., where he continues to push the boundaries of technology in the field of computer vision. His work has garnered attention for its innovative approach to machine learning.

Collaborations

Aman collaborates with talented individuals such as Haoyu Ren and Mostafa El-Khamy, contributing to a dynamic work environment that fosters creativity and innovation.

Conclusion

Aman Raj's contributions to deep machine learning and computer vision exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing the field and improving applications that rely on computer vision.

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