University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > The origins of a quantitative methodology for design of computer vision algorithms

The origins of a quantitative methodology for design of computer vision algorithms

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If you have a question about this talk, please contact Per Kristian Lehre.

The seminar will start with basic properties of probability and quantitative use of conditional notation, including the restrictions on Bayesian methodologies when considered in a frequentist framework. I will then explain how the use of this approach can be used to understand Likelihood as a design principle, and the way that common errors in its use during algorithm design can be identified and avoided.

I will give answers to simple problems which are regularly claimed either impossible or a reason for introducing subjective probability in standard AI texts. I will finish with practical illustrations in more complicated computer vision algorithms intended for robotic, scientific and medical applications.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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