WaldBoost – Learning for Time Constrained Sequential Detection ( Version 1 . 0 )

@inproceedings{Sochman2005WaldBoostL,
  title={WaldBoost – Learning for Time Constrained Sequential Detection ( Version 1 . 0 )},
  author={Jan Sochman and Jǐrı́ Matas},
  year={2005}
}
In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of sequential decision-making. If the false positive and false negative error rates are given, the optimal strategy in terms of the shortest average time to decision (number of measurements used) is the Wald’s sequential probability ratio test (SPRT). We built on the optimal SPRT test and enlarge its capabilities to… CONTINUE READING

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