Analytical method enables efficient collection of data

Researchers at North Carolina State University have developed an algorithm to determine how much data is needed for decision making with minimal error rate. "For example, how would you select the smallest number of features that would allow a robot to differentiate between water and solid ground, based on visual data collected by video?" According to the press release, potential applications include analysis of hyperspectral data in military cameras, medical imaging diagnostics and surveillance for homeland security.

Results of this research are published in a paper, "Constrained Dimensionality Reduction Using A Mixed-Norm Penalty Function With Neural Networks" (Huiwen Zeng and Joel Trussell), in IEEE Transactions on Knowledge and Data Engineering.