Why should the TINA algorithms be any better than anyone elses?
Tina has been designed specifically with the aim of providing a toolkit, not only for solving individual problems in machine vision and medical image analysis, but also for building larger, integrated vision systems. This process requires careful attention to the statistical properties of the data output by any individual module, which may be ignored by groups intent on solving only one specific problem (i.e. you won’t find any Bayes priors being used to fudge the output data in Tina). We strongly believe that this approach is essential for scientific process in our research area.
