Learning to Detect Small Impact Craters

  title={Learning to Detect Small Impact Craters},
  author={Philipp Georg Wetzler and Rie Honda and Brian L. Enke and William J. Merline and Clark R. Chapman and Michael C. Burl},
  journal={2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1},
Machine learning techniques have shown considerable promise for visual inspection tasks such as locating human faces in cluttered scenes. In this paper, we examine the utility of such techniques for the scientifically-important problem of detecting and cataloging impact craters in planetary images gathered by spacecraft. Various supervised learning algorithms, including ensemble methods (bagging and AdaBoost with feed-forward neural networks as base learners), support vector machines (SVM), and… CONTINUE READING
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