nnMobileNe: Rethinking CNN for Retinopathy Research

arXiv:2306.01289v3 Announce Type: replace-cross
Abstract: Over the past few decades, convolutional neural networks (CNNs) have been at the forefront of the detection and tracking of various retinal diseases (RD). Despite their success, the emergence of vision transformers (ViT) in the 2020s has shifted the trajectory of RD model development. The leading-edge performance of ViT-based models in RD can be largely credited to their scalability-their ability to improve as more parameters are added. As a result, ViT-based models tend to outshine …

arxiv cnn cs.cv eess.iv research type