The appearance of a rough surface is affected by the direction from which it is lit and texture classifiers should account for this. We propose a classifier that is robust to ligh...
Mike J. Chantler, Ged McGunnigle, A. Penirschke, M...
We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
In many problems the raw data is already classified according to a variety of features using some linear classification algorithm but needs to be reclassified. We introduce a novel...
Because many real-world problems can be represented and solved as constraint satisfaction problems, the development of effective, efficient constraint solvers is important. A solv...
In this work, we introduce an information-theoreticbased correction term to the likelihood ratio classification method for multiple classes. Under certain conditions, the term is ...