Senior Computer Scientist, Center for Vision Technologies
Clay Spence, Ph.D., is a senior computer scientist in SRI’s Center for Vision Technologies. The focus of his work includes machine learning, patterns of life analysis, object recognition in 3-D data, hyperspectral data processing, change detection in video, video enhancement of navigation of UAV-mounted cameras for surveillance, probabilistic modeling, object/pattern recognition, medical image processing, video signal processing and neurobiological modeling.
Spence holds seven patents and has published more than 40 conference papers, journal articles and book chapters. He was also adjunct professor for Bucks County Community College and Burlington County College, where he taught physics courses and laboratory for calculus-based physics.
Spence holds a Ph.D. in theoretical physics, an M.S. degree in physics, and a B.S. degree (cum laude) in physics from the University of California, Irvine.
Recent publications
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Analyzing hyperspectral images into multiple subspaces using Guassian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low dimensional subspaces, and that these subspaces are more easily estimated from the data than the endmembers
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Analyzing hyperspectral images into multiple subspaces using Gaussian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low-dimensional subspaces, and that these subspaces are more easily estimated from the data than the endmembers.
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Pattern of life analysis for diverse data types
SRI has developed a system to automatically analyze the Pattern of Life of ports, routes and vessels from a large collection of AIS data. The PoL of these entities are characterized by a set of intuitive and easy to query semantic attributes.