Springfield, VA, United States of America

Clifford Clausen


Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 12(Granted Patents)


Company Filing History:


Years Active: 2004

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1 patent (USPTO):Explore Patents

Title: The Innovative Mind of Clifford Clausen

Introduction

Clifford Clausen is a notable inventor based in Springfield, Virginia. He has made significant contributions to the field of image compression through his innovative approach to fractal image compression using reinforcement learning. His work exemplifies the intersection of technology and creativity, showcasing how advanced algorithms can enhance image processing.

Latest Patents

Clausen holds a patent for a method titled "Fractal image compression using reinforcement learning." This invention discloses a novel approach to fractal image compression, where a reinforced learning algorithm enhances the performance of traditional fractal image compression techniques. The algorithm focuses on improving image partitioning and transform family selection while considering the impact of domain to range matching. Unlike other fractal image compression algorithms, Clausen's method generalizes from experience compressing small portions of an image to effectively compressing the entire image.

Career Highlights

Clifford Clausen is affiliated with George Mason University, where he contributes to research and development in the field of image processing. His academic background and professional experience have equipped him with the skills necessary to innovate in this complex area of technology.

Collaborations

Clausen has worked alongside Harry Wechsler, a fellow researcher, to further explore advancements in image compression techniques. Their collaboration highlights the importance of teamwork in driving innovation and achieving breakthroughs in technology.

Conclusion

Clifford Clausen's work in fractal image compression using reinforcement learning represents a significant advancement in the field. His innovative approach not only improves existing algorithms but also sets the stage for future developments in image processing technology.

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