Our dataset includes three parts: MNIST-rot, MNIST-scale, and MNIST-rand.
MNIST-rot is generated by randomly rotating
each sample in the MNIST testing dataset in $[0,2\pi]$.
We generated MNIST-scale by randomly scaling
the ratio of the area occupied by the symbol over that of the entire image by a factor
in $[0.5,1]$, and generated MNIST-rand by scaling and
rotating images in MNIST testing dataset simultaneously.
Access the dataset for images of typical diabetic retinopathy lesions and also normal retinal structures annotated at a pixel level, focused on an Indian population. This dataset provides information on the disease severity of diabetic retinopathy, and diabetic macular edema for each image.