Troy, MI, United States of America

Chitteshwaran Thavamani


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations by Chitteshwaran Thavamani in Autonomous Driving

Introduction

Chitteshwaran Thavamani is an accomplished inventor based in Troy, MI, USA. He has made significant contributions to the field of autonomous driving through his innovative patent. His work focuses on enhancing object detection systems, which are crucial for the development of self-driving vehicles.

Latest Patents

Thavamani holds a patent titled "Systems and methods for generating object detection labels using foveated image magnification for autonomous driving." This patent discloses systems and methods for processing high-resolution images. The methods include generating a saliency map of a received high-resolution image using a saliency model. The saliency map contains a saliency value associated with each pixel of the high-resolution image. The process involves using the saliency map to create an inverse transformation function that maps pixel coordinates in a warped image to those in the high-resolution image. The resulting warped image is a foveated image, which features at least one region with higher resolution than others.

Career Highlights

Chitteshwaran Thavamani is currently employed at Ford Global Technologies, LLC, where he applies his expertise in image processing and autonomous systems. His innovative approach to object detection has the potential to significantly improve the safety and efficiency of autonomous vehicles.

Collaborations

Thavamani collaborates with notable colleagues, including Nicolas Cebron and Deva K Ramanan. Their combined efforts contribute to advancing technologies in the automotive sector.

Conclusion

Chitteshwaran Thavamani's work exemplifies the intersection of innovation and technology in the field of autonomous driving. His contributions through patents and collaborations are paving the way for safer and more efficient self-driving vehicles.

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