Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis

Figure 3

The testing phase of our per-pixel (PP) model. Features are computed as in the training phase. The projection Q is used to transform the features into the subspace determined in the training phase. Maximum a-posteriori estimation, using the posteriors estimated in the training phase, is then used to generate the label.