Bull Creek, Australia

Haari Taplo Kiiveri


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2009

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1 patent (USPTO):Explore Patents

Title: Haari Taplo Kiiveri: Innovator in Hyperspectral Imaging

Introduction

Haari Taplo Kiiveri is a notable inventor based in Bull Creek, Australia. He has made significant contributions to the field of hyperspectral imaging, particularly through his innovative methods for analyzing multispectral image data. His work has implications for various applications, including remote sensing and environmental monitoring.

Latest Patents

Haari Taplo Kiiveri holds a patent for a method of identifying endmember spectral values from hyperspectral image data. This method involves processing multispectral data to obtain a multidimensional simplex, where each vertex corresponds to an endmember spectrum. The process includes estimating mixing proportions for each data value and iteratively refining these estimates until a minimal change in the regularized residual sum of squares is achieved. This innovative approach enhances the accuracy of spectral analysis in complex datasets.

Career Highlights

Kiiveri is associated with the Commonwealth Scientific and Industrial Research Organisation (CSIRO), where he has contributed to advancing research in hyperspectral imaging. His expertise in this area has positioned him as a valuable asset in the scientific community, particularly in projects that require sophisticated data analysis techniques.

Collaborations

Throughout his career, Haari has collaborated with notable colleagues, including Mark Berman and Ryan Lagerstrom. These partnerships have fostered a collaborative environment that encourages innovation and the sharing of ideas in the field of hyperspectral imaging.

Conclusion

Haari Taplo Kiiveri's contributions to the field of hyperspectral imaging through his patented methods demonstrate his commitment to advancing technology in this area. His work continues to influence research and applications in multispectral data analysis.

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