Figure 1.

Ensemble framework of DL-based DR screening system. The preprocessed and the original RGB images are input to ensembles of three and two DL models, respectively, differing in type of architecture and input image size. Each model then produces a set of five probabilities (probs) belonging to each of the five DR classes: none and early, intermediate, severe, and proliferative DR. The 25 total probabilities are then concatenated (grouped) to form a vector of 25 features, which is input to an LMT. The LMT has been trained to decide the DR class based on the totality of the DL inputs and is the final classifier.