Bothell, WA, United States of America

Mayoore Selvarasa Jaiswal


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):

Title: Innovations of Mayoore Selvarasa Jaiswal

Introduction

Mayoore Selvarasa Jaiswal is an accomplished inventor based in Bothell, WA (US). He has made significant contributions to the field of image processing through his innovative patent. His work focuses on enhancing image quality using advanced techniques.

Latest Patents

Mayoore holds a patent for "Synthetic bracketing for exposure correction." This invention discloses systems and methods related to synthetic bracketing for exposure correction. The deep learning-based method produces a set of differently exposed images from a single input image. The images in the set can be combined to create an output image with improved global and local exposure compared to the input image. An image encoder applies learned parameters to each input image to generate a set of image features, including local exposure estimates for various regions of the input image and a low-resolution latent representation. A decoder processes these elements to generate synthesized transformations, resulting in a set of transformed images that correspond to respective target enhancements.

Career Highlights

Mayoore is currently employed at Nvidia Corporation, where he continues to push the boundaries of technology and innovation. His work at Nvidia allows him to collaborate with some of the brightest minds in the industry, contributing to advancements in artificial intelligence and image processing.

Collaborations

Mayoore collaborates with Jan Kautz, a fellow innovator at Nvidia. Their partnership exemplifies the synergy that can be achieved when talented individuals work together towards common goals.

Conclusion

Mayoore Selvarasa Jaiswal's contributions to the field of image processing through his innovative patent demonstrate his expertise and commitment to advancing technology. His work not only enhances image quality but also showcases the potential of deep learning in practical applications.

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