Martha S. Gilmore

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In the era of large scientific data sets, there is an urgent need for methods to automatically prioritize data for review. At the same time, for any automated method to be adopted by scientists, it must make decisions that they can understand and trust. In this paper, we propose Discovery through Eigenbasis Modeling of Uninteresting Data (DEMUD), which uses(More)
—Superpixels are homogeneous image regions comprised of multiple contiguous pixels. Superpixel representations can reduce noise in hyperspectral images by exploiting the spatial contiguity of scene features. This paper combines superpixels with endmember extraction to produce concise mineralogical summaries that assist in browsing large image catalogs.(More)
Robotic aerovehicles, or aerobots, can perform long duration detailed studies of planetary surfaces and atmospheres in three dimensions. Here we explore specific abilities of an aerobot mission to Venus using two concept missions: the Balloon Experiment at Venus (BEV) and the Venus Flyer Robot (VFR). Oscillating between 40 and 60 km altitude, the BEV is(More)
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