ABSTRACT. Counting craters is a fundamental task of planetary sci- ence because it provides the only tool for measuring relative ages of planetary surfaces.
We design and implement a dynamic programming algorithm to search for a relevant feature subset by removing irrelevant features and minimizing a cost objective ...
We design and implement a dynamic programming algorithm to search for a relevant feature subset by removing irrelevant features and minimizing a cost objective ...
ABSTRACT. Counting craters is a fundamental task of planetary sci- ence because it provides the only tool for measuring relative ages of planetary surfaces.
In this paper we present a method that brings together a novel, efficient crater identification algorithm with a data processing pipeline; together they enable ...
In this paper we propose a wrapperbased randomized feature selection method to efficiently se-lect relevant features for crater detection. We design ...
Bibliographic details on Bernoulli trials based feature selection for crater detection.
In this paper, we combine active learning with semi-supervised learning to build an new semi-supervised active class selection system for crater detection from ...
Bernoulli trials based feature selection for crater detection · 1, 2013-12-11, 2.38MB ; Effectiveness of Cybersecurity Competitions · 1, 2013-11-25, 318.48kB ...
Using gray-scale texture features has recently become a new trend in supervised machine learning crater detection algorithms.