  Introducing automated Diabetic Retinopathy (DR) diagnosis into Ethiopia is
still a challenging task, despite recent reports that present trained Deep
Learning (DL) based DR classifiers surpassing manual graders. This is mainly
because of the expensive cost of conventional retinal imaging devices used in
DL based classifiers. Current approaches that provide mobile based binary
classification of DR, and the way towards a cheaper and offline multi-class
classification of DR will be discussed in this paper.
